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醫療保健市場中人工智慧的類型、應用、最終用戶和部署模式—2025-2030 年全球預測

Artificial Intelligence in Healthcare Market by Type, Application, End User, Deployment Mode - Global Forecast 2025-2030
出版日期: | 出版商: 360iResearch | 英文 184 Pages | 商品交期: 最快1-2個工作天內

價格

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預計到 2024 年醫療保健人工智慧市場價值將達到 238.3 億美元，到 2025 年將達到 287.8 億美元，複合年成長率為 22.13%，到 2030 年將達到 791.3 億美元。

主要市場統計數據
基準年2024年 238.3億美元
預計年份：2025年 287.8億美元
預測年份 2030 791.3億美元
複合年成長率（%） 22.13%

人工智慧 (AI) 從根本上重塑醫療保健產業，將尖端技術與臨床專業知識相結合，提供創新解決方案。人工智慧與醫療保健的整合不僅僅意味著技術進步；這也意味著我們使用數據、做出決策和改善患者結果的方式的轉變。在過去的幾年裡，人工智慧已經從一個未來概念發展成為支持診斷、治療計劃和業務效率的重要工具。這種演變受到幾個關鍵因素的推動，包括醫療保健數據的日益普及、機器學習演算法的突破以及在改善患者照護的同時降低成本的迫切需求。

在這個動態的環境中，相關人員——從臨床醫生和 IT 專業人員到政策制定者和研究人員——發現自己正處於一個複雜但充滿機會的環境中。努力保持競爭力的醫療保健組織面臨著提供高品質、個人化護理和確保營運永續性的雙重任務。這是一項策略必要事項，它為慢性病管理開闢了新途徑，簡化了工作流程，並提高了診斷的準確性。

人工智慧在醫療保健領域的變革力量也正在刺激技術創新者和醫療保健提供者之間的合作。這些夥伴關係正在推動支持臨床決策、預測分析和日常業務自動化的先進系統的發展。因此，該領域的持續發展需要即時和長期的策略性投資，為更靈活、高效和以患者為中心的醫療保健系統奠定基礎。

人工智慧主導的醫療保健解決方案的變革時期

隨著人工智慧主導的解決方案成為臨床和業務流程不可或缺的一部分，醫療保健領域正在變革時期。機器學習、自然語言處理和電腦視覺領域的重大進步將提供反應速度更快的系統，從而簡化診斷、個人化治療通訊協定並以前所未有的準確度預測患者結果。此外，人工智慧與醫療保健工作流程的整合正在引發模式轉移。傳統醫療保健正在迅速轉向數位化優先的方法，該方法包括自動化和數據主導的決策。

對患者需求的敏感度現已深深融入技術設計中。該系統旨在提供針對具體情況且高度可操作的即時見解。醫療保健組織正在投資這些下一代工具，以改善病患監測、增強臨床決策支援並最佳化資源分配。這種轉變不僅限於臨床領域；行政和營運領域也從人工智慧主導的效率中受益匪淺，從而降低了開銷並簡化了病患管理。

在臨床測試中，人工智慧不僅可以提高診斷準確性，而且還有助於提高整體護理效率。將先進的數據分析與個人化醫療保健結合，可以產生協同效應，從而提供更快、更可靠的治療結果。在患者期望不斷提高和醫療保健挑戰迅速發展的時代，人工智慧主導的解決方案的這種變革性轉變有可能重塑醫療保健的未來。

詳細的細分洞察推動市場創新

醫療保健人工智慧市場被嚴格細分為多個部分，以便對其多面性提供細緻的理解。富有洞察力的細分方法從各個觀點考慮市場，確保不會忽略任何重要方面。首先，依技術類型分析時，市場大致分為三大類：硬體、服務和軟體。硬體部分深入研究監測設備、機器人和穿戴式裝置的創新，它們在患者照護和診斷準確性方面發揮著獨特的作用。同時，服務部門評估確保人工智慧解決方案無縫運作所需的諮詢服務、部署整合服務和維護支援方面。同時，在軟體領域，我們檢驗臨床決策支援系統、資料管理和分析工具、藥物發現平台、醫療保健影像處理平台和自然語言處理應用程式的開發和實施，每個應用程式都推動增強決策和資料解釋的能力。

為了補充這一點，應用程式細分提供了一個將技術與現實世界的醫療保健流程連接起來的框架。在此背景下，市場從疾病診斷、電子健康記錄(EHR) 管理、病患監測和治療的角度進行審查。人工智慧在疾病診斷中的應用正在進一步完善，重點關注癌症檢測和慢性病管理等關鍵領域，展現出透過早期和有針對性的干涉來挽救生命的潛力。同時，EHR 管理將受益於資料加密和安全以及患者資料分類方面的進步，以確保敏感資訊得到最謹慎的處理。此外，病患監測技術將在遠端患者監護和生命徵象監測方面受到嚴格審查，這反映了業界向優先考慮患者便利的分散護理模式的轉變。最後，治療部分強調了人工智慧在個人化治療方法和新療法開發中的重要性。

醫療保健付款人、醫療保健提供者、患者、製藥公司和生物技術公司等最終用戶的評估進一步豐富了這種詳細的細分。每個團體都對如何採用和利用人工智慧技術來滿足他們的特定需求提供了獨特的見解，無論是控制成本、增強醫療服務還是加速藥物開發。最後，根據雲端基礎、混合和內部部署的解決方案的部署類型進行市場細分，突顯了技術基礎架構的選擇如何推動靈活性和可擴展性。在雲端基礎的類別中，私有雲端和公共雲端解決方案的細微差別得到了仔細考慮，特別是在資料安全性、整合速度和成本效益方面。

這種全面的細分可以對市場趨勢和創新促進因素進行細緻的評估，顯示所有組成部分是如何相互關聯的。透過檢查這些層面，行業領導者可以發現成長機會並根據不斷變化的市場需求調整他們的策略。最終，這些細分洞察提供了對人工智慧應用進展和挑戰的平衡和多方面的視角，推動醫療保健行業走向智慧、個人化和高效的護理未來。

目錄

第1章 引言

第2章調查方法

第3章執行摘要

第4章 市場概述

第5章 市場洞察

  • 市場動態
    • 驅動程式
      • 全球慢性病盛行率不斷上升
      • 擴大人工智慧在臨床決策支援系統中的應用並最大限度地減少診斷錯誤
      • 政府支持將人工智慧融入醫療保健體系的措施和政策
    • 限制因素
      • 將人工智慧工具整合到醫療保健系統中的技術限制
    • 機會
      • 人工智慧整合治療和診斷工具的持續進步
      • 人工智慧在個人化醫療和個人化治療計劃中的作用日益擴大
    • 任務
      • 醫療保健領域人工智慧相關的資料隱私問題和嚴格合規要求
  • 市場區隔分析
    • 類型：臨床決策支援軟體解決方案越來越受歡迎
    • 用途：擴大人工智慧在醫療保健領域疾病診斷的應用
  • 波特五力分析
  • PESTEL分析
    • 政治
    • 經濟
    • 社會
    • 科技
    • 法律
    • 環境

第6章 醫療保健市場中的人工智慧（按類型）

  • 介紹
  • 硬體
    • 監控設備
    • 機器人技術
    • 穿戴式裝置
  • 服務
    • 諮詢服務
    • 實施和整合服務
    • 維護和支援
  • 軟體
    • 臨床決策支援系統
    • 數據管理與分析
    • 藥物研發平台
    • 醫療影像平台
    • 自然語言處理應用

第7章 醫療保健市場中的人工智慧應用

  • 介紹
  • 疾病診斷
    • 癌症檢測
    • 慢性病管理
  • EHR管理
    • 資料加密和安全
    • 患者資料分類
  • 病患監測
    • 遠端患者監護
    • 生命徵象監測
  • 治療

第8章 醫療保健市場中的人工智慧（按最終用戶）

  • 介紹
  • 醫療保險公司
  • 醫療保健提供者
  • 病人
  • 製藥和生物技術公司

第9章醫療保健市場中的人工智慧（按部署模式）

  • 介紹
  • 雲端基礎
    • 私有雲端
    • 公共雲端
  • 混合
  • 本地

10. 美國醫療保健人工智慧市場

  • 介紹
  • 阿根廷
  • 巴西
  • 加拿大
  • 墨西哥
  • 美國

11. 亞太地區醫療保健市場人工智慧

  • 介紹
  • 澳洲
  • 中國
  • 印度
  • 印尼
  • 日本
  • 馬來西亞
  • 菲律賓
  • 新加坡
  • 韓國
  • 台灣
  • 泰國
  • 越南

12. 歐洲、中東和非洲醫療保健市場中的人工智慧

  • 介紹
  • 丹麥
  • 埃及
  • 芬蘭
  • 法國
  • 德國
  • 以色列
  • 義大利
  • 荷蘭
  • 奈及利亞
  • 挪威
  • 波蘭
  • 卡達
  • 俄羅斯
  • 沙烏地阿拉伯
  • 南非
  • 西班牙
  • 瑞典
  • 瑞士
  • 土耳其
  • 阿拉伯聯合大公國
  • 英國

第13章競爭格局

  • 2024年市場佔有率分析
  • 2024年FPNV定位矩陣
  • 競爭情境分析
  • 戰略分析與建議

公司名單

  • AiCure, LLC
  • Atomwise Inc.
  • Babylon Healthcare Services Ltd
  • Behold.ai Technologies Limited
  • Berg LLC
  • Butterfly Network, Inc.
  • ClosedLoop.ai Inc.
  • GE Healthcare
  • Google, LLC by Alphabet, Inc.
  • Intel Corporation
  • International Business Machines Corporation
  • Koninklijke Philips NV
  • Medasense Biometrics Ltd.
  • Microsoft Corporation
  • Modernizing Medicine, Inc.
  • Nanox Imaging Ltd.
  • Novo Nordisk A/S
  • NVIDIA Corporation
  • Oncora Medical
  • Oracle Corporation
  • Oxipit.ai
  • Recursion Pharmaceuticals
  • Sanofi SA
  • Sensely, Inc.
  • Siemens Healthineers AG
  • Tempus Labs, Inc.
Product Code: MRR-031BF22F9550

The Artificial Intelligence in Healthcare Market was valued at USD 23.83 billion in 2024 and is projected to grow to USD 28.78 billion in 2025, with a CAGR of 22.13%, reaching USD 79.13 billion by 2030.

KEY MARKET STATISTICS
Base Year [2024] USD 23.83 billion
Estimated Year [2025] USD 28.78 billion
Forecast Year [2030] USD 79.13 billion
CAGR (%) 22.13%

Artificial Intelligence (AI) has fundamentally reshaped the healthcare industry, merging cutting-edge technology with clinical expertise to offer innovative solutions. The integration of AI in healthcare represents not only a technological advancement but also a transformation in how data is harnessed, decisions are made, and patient outcomes are improved. Over the past few years, AI has moved from a futuristic concept to an essential tool that supports diagnostics, treatment planning, and operational efficiency. This evolution has been driven by several key factors including the increased availability of healthcare data, breakthroughs in machine learning algorithms, and the pressing need to reduce costs while improving patient care.

In this dynamic environment, stakeholders from clinicians and IT professionals to policymakers and researchers find themselves navigating a complex but opportunity-rich landscape. As healthcare organizations strive to remain competitive, they are compelled by the dual mandate of delivering high-quality, personalized care and ensuring operational sustainability. In this context, AI is more than a technological novelty-it is a strategic imperative that opens new avenues for managing chronic diseases, streamlining workflows, and enhancing diagnostic accuracy.

The transformative power of AI in healthcare has also fostered collaborations between technology innovators and healthcare providers. These partnerships are fueling the development of advanced systems capable of supporting clinical decision-making, predictive analytics, and the automation of routine tasks. As such, the ongoing evolution in this domain invites both immediate and long-term strategic investments, laying the foundation for a healthcare system that is more responsive, efficient, and patient-centered.

Transformative Shifts in AI-Driven Healthcare Solutions

The landscape of healthcare is undergoing transformative shifts as AI-driven solutions become integral to clinical and operational processes. Significant advancements in machine learning, natural language processing, and computer vision are now poised to deliver highly responsive systems that streamline diagnostics, personalize treatment protocols, and predict patient outcomes with unprecedented accuracy. Furthermore, the integration of AI into healthcare workflows has catalyzed a paradigm shift; traditional practices are rapidly giving way to digital-first approaches that embrace automation and data-driven decision-making.

Sensitivity to patient needs is now deeply embedded in technology design; systems are being engineered to provide real-time insights that are both context-specific and highly actionable. As healthcare institutions invest in these next-generation tools, they are witnessing improvements in patient monitoring, enhanced clinical decision support, and the optimization of resource allocation. This transformation is not limited to the clinical domain; administrative and operational spheres are also benefiting extensively from AI driven efficiencies that reduce overheads and streamline patient management.

Clinical trials have increasingly demonstrated that AI not only augments diagnostic precision but also contributes to the overall efficiency of care delivery. The evidence is clear: when you combine advanced data analytics with personalized medicine, you create a synergy that leads to faster, more reliable outcomes. In an era marked by increasing patient expectations and rapidly evolving medical challenges, these transformative shifts in AI-driven solutions hold the promise of reimagining the future of healthcare.

Detailed Segmentation Insights Driving Market Innovation

The healthcare AI market is rigorously dissected into multiple segments that provide a nuanced understanding of its multifaceted nature. An insightful segmentation approach considers the market from various perspectives, ensuring no critical aspect is overlooked. First, when analyzing technology by type, the market is broadly studied across three primary categories-hardware, services, and software. The hardware segment delves into innovations such as monitoring equipment, robotics, and wearable devices, each playing a distinct role in patient care and diagnostic precision. Meanwhile, the services category evaluates the dimensions of consulting services, deployment and integration services, and maintenance and support, all of which are essential for ensuring the seamless operationalization of AI solutions. The software domain, on the other hand, examines the development and implementation of clinical decision support systems, data management and analysis tools, drug discovery platforms, medical imaging platforms, and natural language processing applications, each driving forward the capabilities for enhanced decision-making and data interpretation.

Complementing this, the segmentation based on application provides a framework that links technology with real-world healthcare processes. In this context, the market is reviewed through the lens of disease diagnosis, electronic health record (EHR) management, patient monitoring, and therapeutics. The application of AI in disease diagnosis is further refined by focusing on critical areas such as cancer detection and chronic disease management, showcasing the life-saving potential of early and precise interventions. Concurrently, EHR management benefits from advancements in data encryption and security as well as patient data classification, ensuring that sensitive information is handled meticulously. Further, patient monitoring technologies are scrutinized through the facets of remote patient monitoring and vital sign monitoring, reflecting the industry's shift towards decentralized care models that prioritize patient convenience. Lastly, the therapeutics area underscores the importance of AI in developing personalized treatment regimens and novel therapeutic agents.

This in-depth segmentation is further enriched by evaluation based on end users, which include healthcare insurers, healthcare providers, patients, and pharmaceutical as well as biotech companies. Each group offers unique insights into how AI technologies are being adopted and leveraged to meet their respective needs, whether that be cost containment, enhanced care delivery, or accelerated drug development. Finally, the market's segmentation according to deployment mode-spanning cloud-based, hybrid, and on-premise solutions-reveals how technology infrastructure choices are driving flexibility and scalability. Within the cloud-based category, the nuances of private and public cloud solutions are carefully considered, particularly in light of data security, integration speed, and cost efficiencies.

This comprehensive segmentation allows for a granular assessment of market trends and innovation drivers, illustrating a landscape where every component is interconnected. By examining these layers, industry leaders can pinpoint growth opportunities and tailor their strategies in alignment with evolving market demands. Ultimately, these segmentation insights provide a balanced and multifaceted view of the advancements and challenges in AI adoption, propelling the healthcare industry toward a future defined by intelligent, personalized, and efficient care.

Based on Type, market is studied across Hardware, Services, and Software. The Hardware is further studied across Monitoring Equipment, Robotics, and Wearable Devices. The Services is further studied across Consulting Services, Deployment & Integration Services, and Maintenance & Support. The Software is further studied across Clinical Decision Support Systems, Data Management & Analysis, Drug Discovery Platforms, Medical Imaging Platforms, and Natural Language Processing Applications.

Based on Application, market is studied across Disease Diagnosis, EHR Management, Patient Monitoring, and Therapeutics. The Disease Diagnosis is further studied across Cancer Detection and Chronic Disease Management. The EHR Management is further studied across Data Encryption & Security and Patient Data Classification. The Patient Monitoring is further studied across Remote Patient Monitoring and Vital Sign Monitoring.

Based on End User, market is studied across Healthcare Insurers, Healthcare Providers, Patients, and Pharmaceutical & Biotech Companies.

Based on Deployment Mode, market is studied across Cloud-Based, Hybrid, and On-Premise. The Cloud-Based is further studied across Private Cloud and Public Cloud.

Geographic Insights Shaping Global Market Dynamics

A review of geographic markets reveals significant regional trends that are shaping the global adoption of AI in healthcare. In the Americas, healthcare institutions are rapidly incorporating AI technologies driven by robust infrastructure, innovative regulatory policies, and high investment in digital transformation. This region has become a hotbed for pioneering research and early adoption of next-generation medical technologies. Europe, the Middle East, and Africa are also notable; many countries in this combined region are investing in AI to tackle unique challenges such as an aging population and the evolving needs of public healthcare services, while also focusing on regulatory frameworks that promote safe adoption. Similarly, in the Asia-Pacific region, dynamic growth is witnessed as technological advancements are intertwined with an increasing demand for quality healthcare services in both urban and rural settings.

Each of these regions faces its own set of opportunities and challenges. The Americas lead in terms of policy support and high investment flows, paving the way for rapid innovation and market expansion. Meanwhile, Europe, the Middle East, and Africa are becoming more agile with emerging AI projects that emphasize personalized and preventive care, while the Asia-Pacific region's vibrant market is driven by high-volume patient bases and expanding digital health ecosystems. These geographic insights not only highlight the diverse market maturity and readiness levels but also indicate how localized strategies can better align product development with regional needs. The competitive dynamics in one area often spark innovations that ripple across borders, reinforcing the interconnected nature of global healthcare markets.

Based on Region, market is studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas is further studied across Argentina, Brazil, Canada, Mexico, and United States. The United States is further studied across California, Florida, Illinois, New York, Ohio, Pennsylvania, and Texas. The Asia-Pacific is further studied across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Taiwan, Thailand, and Vietnam. The Europe, Middle East & Africa is further studied across Denmark, Egypt, Finland, France, Germany, Israel, Italy, Netherlands, Nigeria, Norway, Poland, Qatar, Russia, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, United Arab Emirates, and United Kingdom.

Leading Companies Influencing Technological Advancements

The arena of AI in healthcare is propelled forward by an array of influential companies that are pushing the boundaries of innovation and redefining clinical practices. Among the notable players are firms such as AiCure, LLC and Atomwise Inc., which have carved out distinctive niches in digital health and drug discovery, respectively. Babylon Healthcare Services Ltd and Behold.ai Technologies Limited stand at the forefront of clinical imaging and diagnostic support, while Berg LLC has introduced groundbreaking approaches in biopharmaceutical development. Companies like Butterfly Network, Inc. and ClosedLoop.ai Inc. serve critical roles by developing user-friendly and scalable solutions that address both patient monitoring and operational efficiency.

Another set of industry leaders, including GE Healthcare, Google, LLC by Alphabet, Inc., and Intel Corporation, are redefining the capabilities of hardware and computing power in clinical settings. Meanwhile, International Business Machines Corporation and Koninklijke Philips N.V. have consistently innovated in medical imaging and data analysis, setting industry benchmarks for quality and precision. Medasense Biometrics Ltd. and Microsoft Corporation further contribute to driving secure, robust technological deployments in patient monitoring and health data management. Modernizing Medicine, Inc. is acclaimed for its specialized software solutions, and Nanox Imaging Ltd. represents a new wave of cost-effective imaging technologies.

Additionally, Novo Nordisk A/S, NVIDIA Corporation, Oncora Medical, Oracle Corporation, and Oxipit.ai are pivotal in integrating advanced analytics with clinical diagnostics and improving therapeutic insights. Recursion Pharmaceuticals and Sanofi SA are aggressively harnessing AI to fast-track drug discovery and development processes. Sensely, Inc., Siemens Healthineers AG, and Tempus Labs, Inc. are further complementing this ecosystem with innovative technologies that emphasize precision medicine and optimized patient care. Collectively, these companies not only set high operational standards but also fuel competition that drives continuous improvement and novel solutions for an evolving healthcare environment.

The report delves into recent significant developments in the Artificial Intelligence in Healthcare Market, highlighting leading vendors and their innovative profiles. These include AiCure, LLC, Atomwise Inc., Babylon Healthcare Services Ltd, Behold.ai Technologies Limited, Berg LLC, Butterfly Network, Inc., ClosedLoop.ai Inc., GE Healthcare, Google, LLC by Alphabet, Inc., Intel Corporation, International Business Machines Corporation, Koninklijke Philips N.V., Medasense Biometrics Ltd., Microsoft Corporation, Modernizing Medicine, Inc., Nanox Imaging Ltd., Novo Nordisk A/S, NVIDIA Corporation, Oncora Medical, Oracle Corporation, Oxipit.ai, Recursion Pharmaceuticals, Sanofi SA, Sensely, Inc., Siemens Healthineers AG, and Tempus Labs, Inc.. Strategic Recommendations for Industry Leaders to Capitalize on Emerging Trends

Industry leaders are well-positioned to harness the transformative potential of AI in healthcare by adopting strategies that emphasize innovation, collaboration, and agile adaptation. It is imperative for decision-makers to prioritize investment in robust data infrastructure as a foundational step to capturing valuable insights from large-scale clinical datasets. Capitalizing on emerging trends requires not only funding technological advancements but also engaging in active alliances with research institutions, tech start-ups, and established healthcare providers to facilitate the seamless integration of AI solutions into existing infrastructures.

Leaders must continuously evaluate the regulatory environment and adapt best practices to ensure data privacy, security, and compliance. Embracing flexible deployment modes such as cloud-based and hybrid systems can provide the agility necessary to scale operations efficiently. Equally important is the commitment to staff training and knowledge enhancement: educating clinical teams and operational personnel about the potential and limitations of AI tools ensures that technology complements human expertise rather than replacing it. A proactive approach in fostering an innovation culture can lead to accelerated adoption and a smoother transition into digital-first healthcare models.

Furthermore, strategic investments in research and development will drive continuous innovation and help differentiate service offerings in a competitive market landscape. Closely monitoring market segmentation insights enables leaders to tailor strategies based on application-specific needs, be it in disease diagnosis, patient monitoring, or therapeutics. Finally, leveraging partnerships with leading technology companies can provide early access to cutting-edge solutions and integrate proven methodologies into healthcare systems. These actionable recommendations, when applied collectively, serve to position organizations at the forefront of the AI revolution in healthcare, ensuring sustainable growth and enhanced patient outcomes.

Final Thoughts on the Impact of AI in Healthcare

The revolution spurred by AI in healthcare marks a turning point in the way medical services are delivered and managed across the globe. Through enhanced diagnostic tools, precise patient monitoring systems, and efficient operational frameworks, the integration of AI is not only reshaping clinical practice but also improving overall quality of care. The advancements discussed herein underscore the significant strides made in technology that drive improved patient outcomes, operational efficiency, and ultimately, the promise of personalized medicine.

Reflecting on the transformative shifts witnessed over the recent years, it is evident that AI is more than a transient trend-it is an entrenched component of modern medical practice. The careful segmentation of the market into various dimensions such as technology type, application, end user, and deployment mode has revealed a landscape that is both diverse and robust. Furthermore, the geographic and company analyses provide a comprehensive understanding of how different regions and industry players are converging towards a common goal of revolutionizing patient care.

In summary, healthcare organizations that successfully integrate AI into their operations will not only meet the growing demands of patients but also achieve significant competitive advantages in an increasingly digital world. The journey towards fully realized AI-driven healthcare is laden with challenges, yet the benefits far outweigh the hurdles-ensuring that every stakeholder, from clinicians to policymakers, reaps the rewards of a smarter, more connected ecosystem.

Table of Contents

1. Preface

  • 1.1. Objectives of the Study
  • 1.2. Market Segmentation & Coverage
  • 1.3. Years Considered for the Study
  • 1.4. Currency & Pricing
  • 1.5. Language
  • 1.6. Stakeholders

2. Research Methodology

  • 2.1. Define: Research Objective
  • 2.2. Determine: Research Design
  • 2.3. Prepare: Research Instrument
  • 2.4. Collect: Data Source
  • 2.5. Analyze: Data Interpretation
  • 2.6. Formulate: Data Verification
  • 2.7. Publish: Research Report
  • 2.8. Repeat: Report Update

3. Executive Summary

4. Market Overview

5. Market Insights

  • 5.1. Market Dynamics
    • 5.1.1. Drivers
      • 5.1.1.1. Rising prevalence of chronic diseases globally
      • 5.1.1.2. Expanding usage of AI in clinical decision support systems and minimizing diagnostic errors
      • 5.1.1.3. Government initiatives and policies supporting integration of AI in healthcare systems
    • 5.1.2. Restraints
      • 5.1.2.1. Technological limitations in integration of AI tools in healthcare systems
    • 5.1.3. Opportunities
      • 5.1.3.1. Ongoing advancements in AI integrated therapeutic and diagnostic tools
      • 5.1.3.2. Expanding role of AI in personalized medicine and tailored treatment plans
    • 5.1.4. Challenges
      • 5.1.4.1. Data privacy concerns and stringent compliance requirements associated with AI in healthcare
  • 5.2. Market Segmentation Analysis
    • 5.2.1. Type: Increasing preference for software solutions for clinical decision support systems
    • 5.2.2. Application: Expanding application of artificial intelligence in healthcare in disease diagnosis
  • 5.3. Porter's Five Forces Analysis
    • 5.3.1. Threat of New Entrants
    • 5.3.2. Threat of Substitutes
    • 5.3.3. Bargaining Power of Customers
    • 5.3.4. Bargaining Power of Suppliers
    • 5.3.5. Industry Rivalry
  • 5.4. PESTLE Analysis
    • 5.4.1. Political
    • 5.4.2. Economic
    • 5.4.3. Social
    • 5.4.4. Technological
    • 5.4.5. Legal
    • 5.4.6. Environmental

6. Artificial Intelligence in Healthcare Market, by Type

  • 6.1. Introduction
  • 6.2. Hardware
    • 6.2.1. Monitoring Equipment
    • 6.2.2. Robotics
    • 6.2.3. Wearable Devices
  • 6.3. Services
    • 6.3.1. Consulting Services
    • 6.3.2. Deployment & Integration Services
    • 6.3.3. Maintenance & Support
  • 6.4. Software
    • 6.4.1. Clinical Decision Support Systems
    • 6.4.2. Data Management & Analysis
    • 6.4.3. Drug Discovery Platforms
    • 6.4.4. Medical Imaging Platforms
    • 6.4.5. Natural Language Processing Applications

7. Artificial Intelligence in Healthcare Market, by Application

  • 7.1. Introduction
  • 7.2. Disease Diagnosis
    • 7.2.1. Cancer Detection
    • 7.2.2. Chronic Disease Management
  • 7.3. EHR Management
    • 7.3.1. Data Encryption & Security
    • 7.3.2. Patient Data Classification
  • 7.4. Patient Monitoring
    • 7.4.1. Remote Patient Monitoring
    • 7.4.2. Vital Sign Monitoring
  • 7.5. Therapeutics

8. Artificial Intelligence in Healthcare Market, by End User

  • 8.1. Introduction
  • 8.2. Healthcare Insurers
  • 8.3. Healthcare Providers
  • 8.4. Patients
  • 8.5. Pharmaceutical & Biotech Companies

9. Artificial Intelligence in Healthcare Market, by Deployment Mode

  • 9.1. Introduction
  • 9.2. Cloud-Based
    • 9.2.1. Private Cloud
    • 9.2.2. Public Cloud
  • 9.3. Hybrid
  • 9.4. On-Premise

10. Americas Artificial Intelligence in Healthcare Market

  • 10.1. Introduction
  • 10.2. Argentina
  • 10.3. Brazil
  • 10.4. Canada
  • 10.5. Mexico
  • 10.6. United States

11. Asia-Pacific Artificial Intelligence in Healthcare Market

  • 11.1. Introduction
  • 11.2. Australia
  • 11.3. China
  • 11.4. India
  • 11.5. Indonesia
  • 11.6. Japan
  • 11.7. Malaysia
  • 11.8. Philippines
  • 11.9. Singapore
  • 11.10. South Korea
  • 11.11. Taiwan
  • 11.12. Thailand
  • 11.13. Vietnam

12. Europe, Middle East & Africa Artificial Intelligence in Healthcare Market

  • 12.1. Introduction
  • 12.2. Denmark
  • 12.3. Egypt
  • 12.4. Finland
  • 12.5. France
  • 12.6. Germany
  • 12.7. Israel
  • 12.8. Italy
  • 12.9. Netherlands
  • 12.10. Nigeria
  • 12.11. Norway
  • 12.12. Poland
  • 12.13. Qatar
  • 12.14. Russia
  • 12.15. Saudi Arabia
  • 12.16. South Africa
  • 12.17. Spain
  • 12.18. Sweden
  • 12.19. Switzerland
  • 12.20. Turkey
  • 12.21. United Arab Emirates
  • 12.22. United Kingdom

13. Competitive Landscape

  • 13.1. Market Share Analysis, 2024
  • 13.2. FPNV Positioning Matrix, 2024
  • 13.3. Competitive Scenario Analysis
    • 13.3.1. HealthEdge and Codoxo join forces to provide healthcare payers with cutting-edge solutions and services
    • 13.3.2. Google Cloud harnesses AI with DeliverHealth to streamline healthcare documentation and support startups
    • 13.3.3. Microsoft's AI innovations aim to enhance clinicians' workloads and enhance system efficiency
    • 13.3.4. GE HealthCare's strategic acquisition leverages AI innovation to transform ultrasound technology
    • 13.3.5. GE HealthCare Launches AI-Powered Innovations to Shape the Future of Healthcare
    • 13.3.6. HEALWELL AI to Acquire Intrahealth to Create Next Generation AI-powered EHR
    • 13.3.7. HEALWELL AI Completes Acquisition of 'Pentavere,' a Healthcare AI and Data Science Company
  • 13.4. Strategy Analysis & Recommendation

Companies Mentioned

  • 1. AiCure, LLC
  • 2. Atomwise Inc.
  • 3. Babylon Healthcare Services Ltd
  • 4. Behold.ai Technologies Limited
  • 5. Berg LLC
  • 6. Butterfly Network, Inc.
  • 7. ClosedLoop.ai Inc.
  • 8. GE Healthcare
  • 9. Google, LLC by Alphabet, Inc.
  • 10. Intel Corporation
  • 11. International Business Machines Corporation
  • 12. Koninklijke Philips N.V.
  • 13. Medasense Biometrics Ltd.
  • 14. Microsoft Corporation
  • 15. Modernizing Medicine, Inc.
  • 16. Nanox Imaging Ltd.
  • 17. Novo Nordisk A/S
  • 18. NVIDIA Corporation
  • 19. Oncora Medical
  • 20. Oracle Corporation
  • 21. Oxipit.ai
  • 22. Recursion Pharmaceuticals
  • 23. Sanofi SA
  • 24. Sensely, Inc.
  • 25. Siemens Healthineers AG
  • 26. Tempus Labs, Inc.

LIST OF FIGURES

  • FIGURE 1. ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET MULTI-CURRENCY
  • FIGURE 2. ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET MULTI-LANGUAGE
  • FIGURE 3. ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET RESEARCH PROCESS
  • FIGURE 4. ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, 2024 VS 2030
  • FIGURE 5. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, 2018-2030 (USD MILLION)
  • FIGURE 6. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY REGION, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 7. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 8. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY TYPE, 2024 VS 2030 (%)
  • FIGURE 9. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY TYPE, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 10. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY APPLICATION, 2024 VS 2030 (%)
  • FIGURE 11. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY APPLICATION, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 12. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY END USER, 2024 VS 2030 (%)
  • FIGURE 13. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY END USER, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 14. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DEPLOYMENT MODE, 2024 VS 2030 (%)
  • FIGURE 15. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DEPLOYMENT MODE, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 16. AMERICAS ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY COUNTRY, 2024 VS 2030 (%)
  • FIGURE 17. AMERICAS ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 18. UNITED STATES ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY STATE, 2024 VS 2030 (%)
  • FIGURE 19. UNITED STATES ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY STATE, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 20. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY COUNTRY, 2024 VS 2030 (%)
  • FIGURE 21. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 22. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY COUNTRY, 2024 VS 2030 (%)
  • FIGURE 23. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY COUNTRY, 2024 VS 2025 VS 2030 (USD MILLION)
  • FIGURE 24. ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SHARE, BY KEY PLAYER, 2024
  • FIGURE 25. ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET, FPNV POSITIONING MATRIX, 2024

LIST OF TABLES

  • TABLE 1. ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SEGMENTATION & COVERAGE
  • TABLE 2. UNITED STATES DOLLAR EXCHANGE RATE, 2018-2024
  • TABLE 3. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, 2018-2030 (USD MILLION)
  • TABLE 4. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 5. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
  • TABLE 6. ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET DYNAMICS
  • TABLE 7. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 8. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY HARDWARE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 9. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY MONITORING EQUIPMENT, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 10. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY ROBOTICS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 11. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY WEARABLE DEVICES, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 12. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 13. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SERVICES, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 14. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY CONSULTING SERVICES, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 15. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DEPLOYMENT & INTEGRATION SERVICES, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 16. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY MAINTENANCE & SUPPORT, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 17. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 18. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SOFTWARE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 19. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY CLINICAL DECISION SUPPORT SYSTEMS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 20. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DATA MANAGEMENT & ANALYSIS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 21. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DRUG DISCOVERY PLATFORMS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 22. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY MEDICAL IMAGING PLATFORMS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 23. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY NATURAL LANGUAGE PROCESSING APPLICATIONS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 24. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 25. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 26. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DISEASE DIAGNOSIS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 27. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY CANCER DETECTION, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 28. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY CHRONIC DISEASE MANAGEMENT, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 29. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DISEASE DIAGNOSIS, 2018-2030 (USD MILLION)
  • TABLE 30. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY EHR MANAGEMENT, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 31. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DATA ENCRYPTION & SECURITY, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 32. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PATIENT DATA CLASSIFICATION, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 33. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY EHR MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 34. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PATIENT MONITORING, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 35. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY REMOTE PATIENT MONITORING, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 36. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY VITAL SIGN MONITORING, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 37. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PATIENT MONITORING, 2018-2030 (USD MILLION)
  • TABLE 38. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY THERAPEUTICS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 39. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 40. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY HEALTHCARE INSURERS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 41. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY HEALTHCARE PROVIDERS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 42. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PATIENTS, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 43. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PHARMACEUTICAL & BIOTECH COMPANIES, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 44. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 45. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY CLOUD-BASED, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 46. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PRIVATE CLOUD, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 47. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PUBLIC CLOUD, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 48. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY CLOUD-BASED, 2018-2030 (USD MILLION)
  • TABLE 49. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY HYBRID, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 50. GLOBAL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY ON-PREMISE, BY REGION, 2018-2030 (USD MILLION)
  • TABLE 51. AMERICAS ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 52. AMERICAS ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 53. AMERICAS ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 54. AMERICAS ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 55. AMERICAS ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 56. AMERICAS ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DISEASE DIAGNOSIS, 2018-2030 (USD MILLION)
  • TABLE 57. AMERICAS ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY EHR MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 58. AMERICAS ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PATIENT MONITORING, 2018-2030 (USD MILLION)
  • TABLE 59. AMERICAS ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 60. AMERICAS ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 61. AMERICAS ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY CLOUD-BASED, 2018-2030 (USD MILLION)
  • TABLE 62. AMERICAS ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
  • TABLE 63. ARGENTINA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 64. ARGENTINA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 65. ARGENTINA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 66. ARGENTINA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 67. ARGENTINA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 68. ARGENTINA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DISEASE DIAGNOSIS, 2018-2030 (USD MILLION)
  • TABLE 69. ARGENTINA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY EHR MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 70. ARGENTINA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PATIENT MONITORING, 2018-2030 (USD MILLION)
  • TABLE 71. ARGENTINA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 72. ARGENTINA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 73. ARGENTINA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY CLOUD-BASED, 2018-2030 (USD MILLION)
  • TABLE 74. BRAZIL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 75. BRAZIL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 76. BRAZIL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 77. BRAZIL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 78. BRAZIL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 79. BRAZIL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DISEASE DIAGNOSIS, 2018-2030 (USD MILLION)
  • TABLE 80. BRAZIL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY EHR MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 81. BRAZIL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PATIENT MONITORING, 2018-2030 (USD MILLION)
  • TABLE 82. BRAZIL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 83. BRAZIL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 84. BRAZIL ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY CLOUD-BASED, 2018-2030 (USD MILLION)
  • TABLE 85. CANADA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 86. CANADA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 87. CANADA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 88. CANADA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 89. CANADA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 90. CANADA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DISEASE DIAGNOSIS, 2018-2030 (USD MILLION)
  • TABLE 91. CANADA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY EHR MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 92. CANADA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PATIENT MONITORING, 2018-2030 (USD MILLION)
  • TABLE 93. CANADA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 94. CANADA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 95. CANADA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY CLOUD-BASED, 2018-2030 (USD MILLION)
  • TABLE 96. MEXICO ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 97. MEXICO ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 98. MEXICO ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 99. MEXICO ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 100. MEXICO ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 101. MEXICO ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DISEASE DIAGNOSIS, 2018-2030 (USD MILLION)
  • TABLE 102. MEXICO ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY EHR MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 103. MEXICO ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PATIENT MONITORING, 2018-2030 (USD MILLION)
  • TABLE 104. MEXICO ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 105. MEXICO ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 106. MEXICO ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY CLOUD-BASED, 2018-2030 (USD MILLION)
  • TABLE 107. UNITED STATES ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 108. UNITED STATES ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 109. UNITED STATES ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 110. UNITED STATES ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 111. UNITED STATES ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 112. UNITED STATES ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DISEASE DIAGNOSIS, 2018-2030 (USD MILLION)
  • TABLE 113. UNITED STATES ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY EHR MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 114. UNITED STATES ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PATIENT MONITORING, 2018-2030 (USD MILLION)
  • TABLE 115. UNITED STATES ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 116. UNITED STATES ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 117. UNITED STATES ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY CLOUD-BASED, 2018-2030 (USD MILLION)
  • TABLE 118. UNITED STATES ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY STATE, 2018-2030 (USD MILLION)
  • TABLE 119. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 120. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 121. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 122. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 123. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 124. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DISEASE DIAGNOSIS, 2018-2030 (USD MILLION)
  • TABLE 125. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY EHR MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 126. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PATIENT MONITORING, 2018-2030 (USD MILLION)
  • TABLE 127. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 128. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 129. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY CLOUD-BASED, 2018-2030 (USD MILLION)
  • TABLE 130. ASIA-PACIFIC ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
  • TABLE 131. AUSTRALIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 132. AUSTRALIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 133. AUSTRALIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 134. AUSTRALIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 135. AUSTRALIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 136. AUSTRALIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DISEASE DIAGNOSIS, 2018-2030 (USD MILLION)
  • TABLE 137. AUSTRALIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY EHR MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 138. AUSTRALIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PATIENT MONITORING, 2018-2030 (USD MILLION)
  • TABLE 139. AUSTRALIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 140. AUSTRALIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 141. AUSTRALIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY CLOUD-BASED, 2018-2030 (USD MILLION)
  • TABLE 142. CHINA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 143. CHINA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 144. CHINA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 145. CHINA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 146. CHINA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 147. CHINA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DISEASE DIAGNOSIS, 2018-2030 (USD MILLION)
  • TABLE 148. CHINA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY EHR MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 149. CHINA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PATIENT MONITORING, 2018-2030 (USD MILLION)
  • TABLE 150. CHINA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 151. CHINA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 152. CHINA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY CLOUD-BASED, 2018-2030 (USD MILLION)
  • TABLE 153. INDIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 154. INDIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 155. INDIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 156. INDIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 157. INDIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 158. INDIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DISEASE DIAGNOSIS, 2018-2030 (USD MILLION)
  • TABLE 159. INDIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY EHR MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 160. INDIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PATIENT MONITORING, 2018-2030 (USD MILLION)
  • TABLE 161. INDIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 162. INDIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 163. INDIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY CLOUD-BASED, 2018-2030 (USD MILLION)
  • TABLE 164. INDONESIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 165. INDONESIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 166. INDONESIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 167. INDONESIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 168. INDONESIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 169. INDONESIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DISEASE DIAGNOSIS, 2018-2030 (USD MILLION)
  • TABLE 170. INDONESIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY EHR MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 171. INDONESIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PATIENT MONITORING, 2018-2030 (USD MILLION)
  • TABLE 172. INDONESIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 173. INDONESIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 174. INDONESIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY CLOUD-BASED, 2018-2030 (USD MILLION)
  • TABLE 175. JAPAN ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 176. JAPAN ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 177. JAPAN ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 178. JAPAN ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 179. JAPAN ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 180. JAPAN ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DISEASE DIAGNOSIS, 2018-2030 (USD MILLION)
  • TABLE 181. JAPAN ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY EHR MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 182. JAPAN ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PATIENT MONITORING, 2018-2030 (USD MILLION)
  • TABLE 183. JAPAN ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 184. JAPAN ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 185. JAPAN ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY CLOUD-BASED, 2018-2030 (USD MILLION)
  • TABLE 186. MALAYSIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 187. MALAYSIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 188. MALAYSIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 189. MALAYSIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 190. MALAYSIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 191. MALAYSIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DISEASE DIAGNOSIS, 2018-2030 (USD MILLION)
  • TABLE 192. MALAYSIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY EHR MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 193. MALAYSIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PATIENT MONITORING, 2018-2030 (USD MILLION)
  • TABLE 194. MALAYSIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 195. MALAYSIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 196. MALAYSIA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY CLOUD-BASED, 2018-2030 (USD MILLION)
  • TABLE 197. PHILIPPINES ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 198. PHILIPPINES ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 199. PHILIPPINES ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 200. PHILIPPINES ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 201. PHILIPPINES ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 202. PHILIPPINES ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DISEASE DIAGNOSIS, 2018-2030 (USD MILLION)
  • TABLE 203. PHILIPPINES ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY EHR MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 204. PHILIPPINES ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PATIENT MONITORING, 2018-2030 (USD MILLION)
  • TABLE 205. PHILIPPINES ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 206. PHILIPPINES ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 207. PHILIPPINES ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY CLOUD-BASED, 2018-2030 (USD MILLION)
  • TABLE 208. SINGAPORE ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 209. SINGAPORE ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 210. SINGAPORE ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 211. SINGAPORE ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 212. SINGAPORE ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 213. SINGAPORE ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DISEASE DIAGNOSIS, 2018-2030 (USD MILLION)
  • TABLE 214. SINGAPORE ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY EHR MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 215. SINGAPORE ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PATIENT MONITORING, 2018-2030 (USD MILLION)
  • TABLE 216. SINGAPORE ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 217. SINGAPORE ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 218. SINGAPORE ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY CLOUD-BASED, 2018-2030 (USD MILLION)
  • TABLE 219. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 220. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 221. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 222. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 223. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 224. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DISEASE DIAGNOSIS, 2018-2030 (USD MILLION)
  • TABLE 225. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY EHR MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 226. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PATIENT MONITORING, 2018-2030 (USD MILLION)
  • TABLE 227. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 228. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 229. SOUTH KOREA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY CLOUD-BASED, 2018-2030 (USD MILLION)
  • TABLE 230. TAIWAN ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 231. TAIWAN ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 232. TAIWAN ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 233. TAIWAN ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 234. TAIWAN ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 235. TAIWAN ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DISEASE DIAGNOSIS, 2018-2030 (USD MILLION)
  • TABLE 236. TAIWAN ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY EHR MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 237. TAIWAN ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PATIENT MONITORING, 2018-2030 (USD MILLION)
  • TABLE 238. TAIWAN ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 239. TAIWAN ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 240. TAIWAN ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY CLOUD-BASED, 2018-2030 (USD MILLION)
  • TABLE 241. THAILAND ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 242. THAILAND ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 243. THAILAND ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 244. THAILAND ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 245. THAILAND ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 246. THAILAND ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DISEASE DIAGNOSIS, 2018-2030 (USD MILLION)
  • TABLE 247. THAILAND ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY EHR MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 248. THAILAND ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PATIENT MONITORING, 2018-2030 (USD MILLION)
  • TABLE 249. THAILAND ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 250. THAILAND ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 251. THAILAND ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY CLOUD-BASED, 2018-2030 (USD MILLION)
  • TABLE 252. VIETNAM ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 253. VIETNAM ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 254. VIETNAM ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 255. VIETNAM ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 256. VIETNAM ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 257. VIETNAM ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DISEASE DIAGNOSIS, 2018-2030 (USD MILLION)
  • TABLE 258. VIETNAM ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY EHR MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 259. VIETNAM ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PATIENT MONITORING, 2018-2030 (USD MILLION)
  • TABLE 260. VIETNAM ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 261. VIETNAM ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 262. VIETNAM ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY CLOUD-BASED, 2018-2030 (USD MILLION)
  • TABLE 263. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 264. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 265. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 266. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 267. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 268. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DISEASE DIAGNOSIS, 2018-2030 (USD MILLION)
  • TABLE 269. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY EHR MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 270. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PATIENT MONITORING, 2018-2030 (USD MILLION)
  • TABLE 271. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 272. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 273. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY CLOUD-BASED, 2018-2030 (USD MILLION)
  • TABLE 274. EUROPE, MIDDLE EAST & AFRICA ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY COUNTRY, 2018-2030 (USD MILLION)
  • TABLE 275. DENMARK ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 276. DENMARK ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 277. DENMARK ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 278. DENMARK ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 279. DENMARK ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 280. DENMARK ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DISEASE DIAGNOSIS, 2018-2030 (USD MILLION)
  • TABLE 281. DENMARK ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY EHR MANAGEMENT, 2018-2030 (USD MILLION)
  • TABLE 282. DENMARK ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY PATIENT MONITORING, 2018-2030 (USD MILLION)
  • TABLE 283. DENMARK ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY END USER, 2018-2030 (USD MILLION)
  • TABLE 284. DENMARK ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DEPLOYMENT MODE, 2018-2030 (USD MILLION)
  • TABLE 285. DENMARK ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY CLOUD-BASED, 2018-2030 (USD MILLION)
  • TABLE 286. EGYPT ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY TYPE, 2018-2030 (USD MILLION)
  • TABLE 287. EGYPT ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY HARDWARE, 2018-2030 (USD MILLION)
  • TABLE 288. EGYPT ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SERVICES, 2018-2030 (USD MILLION)
  • TABLE 289. EGYPT ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY SOFTWARE, 2018-2030 (USD MILLION)
  • TABLE 290. EGYPT ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY APPLICATION, 2018-2030 (USD MILLION)
  • TABLE 291. EGYPT ARTIFICIAL INTELLIGENCE IN HEALTHCARE MARKET SIZE, BY DISEASE DIAGNOSI