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市場調查報告書
商品編碼
1371904

到 2030 年遠端患者監護領域人工智慧市場預測：按產品、解決方案、技術和地區分類的全球分析

Artificial Intelligence In Remote Patient Monitoring Market Forecasts to 2030 - Global Analysis By Product (Vital Monitors, Special Monitors and Other Products), Solution, Technology and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，2023 年全球遠端患者監護人工智慧市場規模達 14 億美元，預計預測期內年複合成長率為 27.8%，到 2030 年將達到 77 億美元。

遠端患者監護(RPM)，有時也稱為人工智慧 (AI)，是使用人工智慧和相關技術遠端監測患者健康狀況的過程。透過利用各種感測器、小工具和數位平台，該技術使醫療保健專業人員能夠追蹤患者的健康狀況，而無需定期親自就診。人工智慧透過自動化資料分析、提供預測性見解以及實現更個人化和主動的醫療保健來提高 RPM。當發現重大變化或異常時，人工智慧驅動的 RPM 系統可以向醫療保健提供者發送警報和通知。這些通知允許及時干涉。

根據美國疾病管制與預防中心 (CDC) 的數據，美國有超過 1,820 萬名 20 歲及以上的成年人患有冠狀動脈疾病。

提高藥物依從性

在遠端患者監護(RPM) 的背景下，人工智慧 (AI) 可以顯著提高用藥依從性。醫療保健中的一個主要問題是藥物不依從性，這會降低治療效果並增加支出。在人工智慧的支援下，RPM 系統可以透過各種媒體（包括行動應用程式、簡訊和電子郵件）向患者發送個人化用藥提醒。患者會發現更容易記住按照指示服藥，根據他們的服藥時間表量身定做。為了製定個體化的藥物計劃，人工智慧可以檢查患者的醫學背景、當前的健康狀況和用藥習慣。此類計劃透過考慮給藥頻率、藥物交互作用和潛在副作用等因素，確保患者獲得最佳的治療建議。因此，所有上述要素都將在整個預測期內推動市場成長。

資料安全和隱私

患者健康資訊極為敏感，披露這些資訊可能會產生不良後果。 RPM 中的 AI 依賴患者資料的收集和傳輸，因此容易受到入侵和資料外洩。由於加密技術薄弱和安全措施詐欺，患者資訊可能容易受到未經授權的訪問，從而使患者隱私面臨風險，因為資料可能被未經授權的人員訪問。因此，除非經過精心規劃和維護，人工智慧系統可能會為不同的病患小組提供不同程度的護理和診斷準確性，從而加劇醫療保健不平等。因此，上述所有要素都阻礙了市場的成長。

降低成本、經濟

人工智慧驅動的遠端監控可以檢測健康狀況下降的早期預警並實現快速介入。這減少了住院的需要，特別是慢性病管理和術後護理。透過避免因非緊急問題而去急診室，透過遠端監控進行早期診斷和介入可以減少對緊急醫療服務的需求。長期成本節約和改善的醫療結果使人工智慧遠端監控成為尋求最佳化醫療服務和降低成本的醫療保健提供者和付款人的有吸引力的選擇。

基於人工智慧的遠端監控解決方案在低收入和中等收入國家尚未得到充分採用

人工智慧 (AI) 已成為醫療保健行業的強大工具，有可能徹底改變患者照護、降低成本並改善結果。雖然基於人工智慧的 RPM 解決方案在高所得國家迅速普及，但在中低收入國家 (LMIC) 的採用率仍然相對較低。中低收入國家的醫療保健預算通常很緊張，因此分配資金來購買和實施昂貴的基於人工智慧的 RPM 系統可能很困難。在一些低收入和中等收入國家，擁有足夠的醫院、診所和經過必要培訓的醫療專業人員可能很困難，阻礙了市場成長。

COVID-19 的影響

COVID-19 的爆發促進了遠端患者監測設備的使用。該國政府在疫情期間實施了旅行限制，迫切需要實施遠端患者監護服務。此外，醫療保健公司透過提供大量用於遠距疾病監測的醫療設備來快速應對 COVID-19 情況。例如，為了減少患者互動並遠端管理健康，美國食品藥物管理局(美國 FDA) 於 2020 年 4 月核准Dexcom 和 Abbott 在醫院提供連續血糖監測設備。

生命監視器細分市場預計將在預測期內成為最大的細分市場

在生命監視器領域，搭載人工智慧的生命徵象監視器可以遠端評估患者的健康狀況，目的是持續或零星地收集和評估患者的各種生理指標，預計將有良好的成長。這些監測儀持續或零星地收集和評估患者的各種生理指標，使醫療保健專業人員能夠及早干涉並在適當的時候獲得重要的見解。Masu。為了追蹤患者的心率，人工智慧系統可以檢查心電圖 (ECG)資料或脈搏波形。如果您的心臟有心律不整，則可以使用袖帶裝置或光電血壓計 (PPG) 等非侵入性技術來監測收縮壓和舒張壓。因此，重要的監視器部門正在推動市場的成長。

機器學習領域預計在預測期內年複合成長率最高

由於人工智慧的一個領域機器學習（ML）顯著提高了 RPM 系統的有效性和效率，因此機器學習領域預計在預測期內將出現最高的年複合成長率年成長率。大量患者資料，包括生命徵象、感測器讀數和電子健康記錄，均由機器學習演算法進行專業處理。這些演算法可以發現人類看護者可能會錯過的模式和趨勢。例如，機器學習可以識別生命徵象的細微變化，並發出健康狀況惡化或潛在緊急情況的訊號。根據歷史資料，機器學習模型可以預測患者的治療結果。透過檢查患者記錄和病歷，這些模型可以預測疾病進展、再入院和不利事件的可能性。這使得醫療保健專業人員能夠提供個人化的護理計劃並主動干涉。

佔比最大的地區：

由於有利的法律​​體系、充足的醫療基礎設施以及人工智慧設備的快速採用，預計歐洲在預測期內將佔據最大的市場佔有率。此外，這些人工智慧輔助監測設備在該地區的部署得到了公司之間策略聯盟的支持，為患者提供完整的遠端患者監護，這將提高接受度。例如，MTech Mobility 和 GenieMD 於 2021 年 8 月簽訂了合作夥伴協議，透過為客戶提供廣泛的遠端患者監護選項來加強該地區的市場成長。

複合年複合成長率最高的地區：

預計北美在預測期內將經歷最高的年複合成長率。這是因為許多變數正在推動北美的持續擴張，包括高齡化、慢性病的增加以及對負擔得起的醫療保健解決方案的需求。 COVID-19 大流行也加速了遠距患者監護技術的引入。北美的許多公司正在積極致力於開發人工智慧主導的應用程式，用於遠端患者監護。其中包括知名的醫療保健IT公司以及專注於人工智慧的新興醫療保健公司。人工智慧主導的RPM 解決方案與北美遠端醫療服務的擴展是相輔相成的。

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訂閱此報告的客戶將收到以下免費自訂選項之一：

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  • 區域分割
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    • 根據產品系列、地理分佈和策略聯盟對主要企業基準化分析

目錄

第1章 執行摘要

第2章 前言

  • 概述
  • 利害關係人
  • 調查範圍
  • 調查方法
    • 資料探勘
    • 資料分析
    • 資料檢驗
    • 研究途徑
  • 調查來源
    • 主要調查來源
    • 二次調查來源
    • 先決條件

第3章 市場趨勢分析

  • 促進因素
  • 抑制因素
  • 機會
  • 威脅
  • 產品分析
  • 技術分析
  • 應用分析
  • 新興市場
  • 新型冠狀病毒感染疾病（COVID-19）的影響

第4章 波特五力分析

  • 供應商的議價能力
  • 買方議價能力
  • 替代的威脅
  • 新進入者的威脅
  • 競爭公司之間的敵對關係

第5章 遠距病患監護市場中的全球人工智慧：依產品

  • 生命監測儀
    • 腦部監視器
    • 脈搏血氧儀
    • 溫度監控器
    • 呼吸監測儀
    • 血壓監測儀
    • 心率監測器
  • 特殊監視器
    • 血糖監測儀
    • 多參數監視器
    • 凝血酶原監測儀
    • 心律監測器
    • 胎心率監測儀
    • 麻醉監控器
  • 其他產品

第6章 遠距患者監護市場中的全球人工智慧：按解決方案

  • 軟體
  • 硬體
  • 服務

第7章 遠距病患監護市場中的全球人工智慧：按技術分類

  • 自然語言處理
  • 機器學習
  • 如何聯絡方式
  • 語音辨識

第8章 全球人工智慧在遠距患者監護市場的應用：按應用分類

  • 糖尿病
  • 呼吸系統的問題
  • 體重管理和健身監測
  • 癌症
  • 脫水
  • 心血管疾病
  • 睡眠失調
  • 病毒感染
  • 其他用途

第11章全球人工智慧遠距患者監護市場：按地區

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲國家
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 其他亞太地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地區
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲

第12章進展

  • 合約、夥伴關係、協作和合資企業
  • 收購和合併
  • 新產品發布
  • 業務擴展
  • 其他關鍵策略

第13章公司簡介

  • Koninklijke Philips NV
  • Medtronic
  • GE Healthcare
  • Abbott Laboratories
  • Resideo Life Care Solutions
  • Cardiomo Care, Inc.
  • Current Health Limited
  • Biofourmis Inc.
  • CU-BX Automotive Technologies Ltd.
  • AiCure, LLC
  • Binah.ai
  • ChroniSense Medical, Ltd.
  • Huma Therapeutics Limited
  • Feebris Ltd.
  • iRhythm Technologies, Inc.
  • iHealth Labs, Inc.
  • Gyant.com, Inc.
  • Myia Labs Inc.
  • iBeat, Inc.
  • Neteera Technologies Ltd.
  • VivaLNK Inc.
Product Code: SMRC23961

According to Stratistics MRC, the Global Artificial Intelligence In Remote Patient Monitoring Market is accounted for $1.4 billion in 2023 and is expected to reach $7.7 billion by 2030 growing at a CAGR of 27.8% during the forecast period. Remote patient monitoring (RPM), sometimes known as artificial intelligence (AI), is the process of remotely monitoring a patient's health using AI and related technologies. By utilizing a variety of sensors, gadgets, and digital platforms, this technology enables healthcare professionals to track a patient's health state without the need for regular in-person visits. By automating data analysis, offering predictive insights, and enabling more individualized and pro-active healthcare, AI improves RPM. When significant changes or anomalies are found, RPM systems with AI can send alerts and notifications to healthcare providers. Timely intervention is made possible by these notifications.

According to the Centers for Disease Control and Prevention (CDC), more than 18.2 million adults aged 20 and above have coronary artery disease in the U.S.

Market Dynamics:

Driver:

Improved medication adherence

In the context of Remote Patient Monitoring (RPM), artificial intelligence (AI) significantly improves medication adherence. A major problem in healthcare is medication non-adherence, which reduces the efficacy of treatment and raises expenditures. Personalized medication reminders can be sent to patients by AI-powered RPM systems via a variety of media, including mobile apps, text messages, or emails. The patient will find it easier to remember to take their meds as directed, which are customized to the patient's medication schedule. To develop individualized pharmaceutical plans, AI can examine a patient's medical background, present health, and drug routine. These plans ensure that patients receive the best possible treatment recommendations by taking into account elements like dose frequency, pharmaceutical interactions, and potential side effects. Hence all the above factors boost the market growth throughout the extrapolated period.

Restraint:

Data security and privacy

Patient health information is extremely sensitive, and any disclosure of this information may have negative effects. AI in RPM is susceptible to intrusions and data breaches since it relies on gathering and transferring patient data. Patient information may be vulnerable to unauthorized access due to weak encryption techniques or insufficient security measures and the data could potentially be accessed by unauthorized people, putting patients' privacy at risk. RPM's AI algorithms could pick up biases from the training data, which could result in disparate healthcare results for various racial and ethnic groups thus AI systems may worsen healthcare inequities by offering varying degrees of care or diagnostic accuracy for various patient groups if they are not carefully planned and maintained. Thus, all the above factors hamper the growth of the market.

Opportunity:

Cost saving and economical

Remote monitoring driven by AI can spot early warning indications of health decline, enabling prompt interventions. This lessens the need for hospital hospitalizations, especially for the management of chronic diseases and post-operative care. By preventing trips to the emergency department for non-urgent problems, early diagnosis and intervention through remote monitoring can lessen the demand on emergency healthcare services. The long-term cost savings and improved healthcare outcomes make AI in Remote Monitoring an appealing choice for healthcare providers and payers looking to optimize healthcare delivery and cut costs, even though the initial investment in AI technology and infrastructure may be necessary.

Threat:

Low and middle-income countries lack the deployment of artificial intelligence-based remote monitoring solutions

Artificial intelligence (AI) has become a potent tool in the healthcare industry with the potential to revolutionize patient care, cut costs, and enhance outcomes. While AI-based RPM solutions have quickly taken off in high-income nations, their adoption in low- and middle-income nations (LMICs) is still relatively low. The allocation of funding for the purchase and deployment of AI-based RPM systems, which can be expensive, might be difficult in LMICs because healthcare budgets there are frequently tight. Having sufficient hospitals, clinics, and medical professionals with the necessary training can be difficult in some low- and middle-income nations which impedes the market growth.

COVID-19 Impact

The COVID-19 epidemic has pushed the use of gadgets for patient remote monitoring due to the country's government's travel limitations during the pandemic, implementing remote patient monitoring services became urgently necessary. Additionally, healthcare businesses responded quickly to the COVID-19 scenario by providing a huge number of medical gadgets for remote sickness monitoring. For instance, in order to reduce patient interaction and manage health remotely, the U.S. Food and Drug Administration (U.S. FDA) approved Dexcom and Abbott to offer continuous glucose monitoring devices in hospitals in April 2020.

The vital monitors segment is expected to be the largest during the forecast period

The vital monitors segment is estimated to have a lucrative growth, as remote assessment of a patient's health status is made possible by AI-powered vital sign monitors, which are meant to continuously or sporadically collect and evaluate a variety of physiological indicators from patients. When appropriate, these monitors can let healthcare professionals intervene early and with significant insights. To track a patient's heart rate, AI systems might examine electrocardiogram (ECG) data or pulse waveforms. It is possible to monitor both systolic and diastolic blood pressure using cuff-based devices or non-invasive techniques like photoplethysmography (PPG) when there are irregularities in heart rhythm. Hence vital monitor segment contributes to the enhancing growth of the market.

The machine learning segment is expected to have the highest CAGR during the forecast period

The machine learning segment is anticipated to witness the highest CAGR growth during the forecast period, as the effectiveness and efficiency of RPM systems are significantly improved by machine learning (ML), a branch of artificial intelligence. Large amounts of patient data, including vital signs, sensor readings, and electronic medical records, are processed expertly by machine learning algorithms. These algorithms can spot patterns and trends that human caregivers might overlook. For instance, ML can identify small alterations in vital signs that signal a person's health is worsening or a potential medical emergency. Based on past data, ML models can predict the outcomes of patients. These models can forecast disease progression, hospital readmissions, or the likelihood of adverse events by studying patient records and medical histories. This enables healthcare professionals to deliver individualized care plans and intervene pro-actively.

Region with largest share:

Europe is projected to hold the largest market share during the forecast period owing to good legislative conditions, the presence of a sufficient healthcare infrastructure, and the quick uptake of the AI devices, Europe retained the largest share in the market. Additionally, the rollout of these AI assisted monitoring devices in the region is being aided by strategic alliances amongst the businesses to offer patients complete remote patient monitoring, which will increase acceptance. For instance, MTech Mobility and GenieMD signed a partnership agreement in August 2021 to offer their customers a wide range of remote patient monitoring options which are enhancing the market growth in this region.

Region with highest CAGR:

North America is projected to have the highest CAGR over the forecast period, owing to a number of variables, such as an aging population, an increase in chronic diseases, and the demand for affordable healthcare solutions, have contributed to North America's continuous expansion. The COVID-19 epidemic has also sped up the introduction of technologies for remote patient monitoring. A number of businesses in North America are actively working to develop AI-driven applications for remote patient monitoring. These include both well-known healthcare IT firms and emerging AI-focused healthcare businesses. AI-driven RPM solutions and the expansion of telehealth services in North America work in harmony.

Key players in the market

Some of the key players profiled in the Artificial Intelligence In Remote Patient Monitoring Market include: Koninklijke Philips N.V., Medtronic, GE Healthcare, Abbott Laboratories, Resideo Life Care Solutions, Cardiomo Care, Inc., Current Health Limited, Biofourmis Inc., CU-BX Automotive Technologies Ltd., AiCure, LLC, Binah.ai, ChroniSense Medical, Ltd., Huma Therapeutics Limited, Feebris Ltd., iRhythm Technologies, Inc., iHealth Labs, Inc., Gyant.com, Inc., Myia Labs Inc., iBeat, Inc., Neteera Technologies Ltd. and VivaLNK Inc.

Key Developments:

In September 2023, Medtronic Diabetes announces CE Mark for new Simplera™ CGM with disposable all-in-one design. The company's newest no-fingerstick sensor does not require over tape and is seamlessly integrated with the InPen™ smart insulin pen, which provides real-time, personalized dosing guidance

In June 2023, Medtronic presents new data on MiniMed™ 780G system on fixed meal dosing and real-world Time in Range across wide variety of users. hese latest results were presented this weekend at the 83rd American Diabetes Association (ADA) Scientific Sessions in San Diego, CA.

In June 2023, Philips and Masimo introduce new, advanced monitoring capabilities to Philips high acuity patient monitors. The latest extension of Masimo and Philips' ongoing collaboration will help enable clinicians to make quick and informed decisions without the need for additional monitoring equipment.

In May 2023, Philips launches AI-powered CT system to accelerate routine radiology and high-volume screening programs. Powered by AI, the Philips CT 3500 includes a range of image-reconstruction and workflow-enhancing features that help to deliver the consistency, speed, and first-time-right image quality

Products Covered:

  • Vital Monitors
  • Special Monitors
  • Other Products

Solutions Covered:

  • Software
  • Hardware
  • Services

Technologies Covered:

  • Natural Language Processing
  • Machine Learning
  • Querying Method
  • Speech Recognition

Applications Covered:

  • Diabetes
  • Respiratory Issues
  • Weight Management & Fitness Monitoring
  • Cancer
  • Dehydration
  • Cardiovascular Diseases
  • Sleep Disorder
  • Viral Infection
  • Other Applications

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2021, 2022, 2023, 2026, and 2030
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Product Analysis
  • 3.7 Technology Analysis
  • 3.8 Application Analysis
  • 3.9 Emerging Markets
  • 3.10 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Artificial Intelligence In Remote Patient Monitoring Market, By Product

  • 5.1 Introduction
  • 5.2 Vital Monitors
    • 5.2.1 Brain Monitor
    • 5.2.2 Pulse Oximeter
    • 5.2.3 Temperature Monitor
    • 5.2.4 Respiratory Monitor
    • 5.2.5 Blood Pressure Monitor
    • 5.2.6 Heart Rate Monitor
  • 5.3 Special Monitors
    • 5.3.1 Blood Glucose Monitor
    • 5.3.2 Multi-Parameter Monitors
    • 5.3.3 Prothrombin Monitors
    • 5.3.4 Cardiac Rhythm Monitor
    • 5.3.5 Fetal Heart Rate Monitor
    • 5.3.6 Anaesthesia Monitors
  • 5.4 Other Products

6 Global Artificial Intelligence In Remote Patient Monitoring Market, By Solution

  • 6.1 Introduction
  • 6.2 Software
  • 6.3 Hardware
  • 6.4 Services

7 Global Artificial Intelligence In Remote Patient Monitoring Market, By Technology

  • 7.1 Introduction
  • 7.2 Natural Language Processing
  • 7.3 Machine Learning
  • 7.4 Querying Method
  • 7.5 Speech Recognition

8 Global Artificial Intelligence In Remote Patient Monitoring Market, By Application

  • 8.1 Introduction
  • 8.2 Diabetes
  • 8.3 Respiratory Issues
  • 8.4 Weight Management & Fitness Monitoring
  • 8.5 Cancer
  • 8.6 Dehydration
  • 8.7 Cardiovascular Diseases
  • 8.8 Sleep Disorder
  • 8.9 Viral Infection
  • 8.10 Other Applications

11 Global Artificial Intelligence In Remote Patient Monitoring Market, By Geography

  • 11.1 Introduction
  • 11.2 North America
    • 11.2.1 US
    • 11.2.2 Canada
    • 11.2.3 Mexico
  • 11.3 Europe
    • 11.3.1 Germany
    • 11.3.2 UK
    • 11.3.3 Italy
    • 11.3.4 France
    • 11.3.5 Spain
    • 11.3.6 Rest of Europe
  • 11.4 Asia Pacific
    • 11.4.1 Japan
    • 11.4.2 China
    • 11.4.3 India
    • 11.4.4 Australia
    • 11.4.5 New Zealand
    • 11.4.6 South Korea
    • 11.4.7 Rest of Asia Pacific
  • 11.5 South America
    • 11.5.1 Argentina
    • 11.5.2 Brazil
    • 11.5.3 Chile
    • 11.5.4 Rest of South America
  • 11.6 Middle East & Africa
    • 11.6.1 Saudi Arabia
    • 11.6.2 UAE
    • 11.6.3 Qatar
    • 11.6.4 South Africa
    • 11.6.5 Rest of Middle East & Africa

12 Key Developments

  • 12.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 12.2 Acquisitions & Mergers
  • 12.3 New Product Launch
  • 12.4 Expansions
  • 12.5 Other Key Strategies

13 Company Profiling

  • 13.1 Koninklijke Philips N.V.
  • 13.2 Medtronic
  • 13.3 GE Healthcare
  • 13.4 Abbott Laboratories
  • 13.5 Resideo Life Care Solutions
  • 13.6 Cardiomo Care, Inc.
  • 13.7 Current Health Limited
  • 13.8 Biofourmis Inc.
  • 13.9 CU-BX Automotive Technologies Ltd.
  • 13.10 AiCure, LLC
  • 13.11 Binah.ai
  • 13.12 ChroniSense Medical, Ltd.
  • 13.13 Huma Therapeutics Limited
  • 13.14 Feebris Ltd.
  • 13.15 iRhythm Technologies, Inc.
  • 13.16 iHealth Labs, Inc.
  • 13.17 Gyant.com, Inc.
  • 13.18 Myia Labs Inc.
  • 13.19 iBeat, Inc.
  • 13.20 Neteera Technologies Ltd.
  • 13.21 VivaLNK Inc.

List of Tables

  • Table 1 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Region (2021-2030) ($MN)
  • Table 2 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Product (2021-2030) ($MN)
  • Table 3 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Vital Monitors (2021-2030) ($MN)
  • Table 4 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Brain Monitor (2021-2030) ($MN)
  • Table 5 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Pulse Oximeter (2021-2030) ($MN)
  • Table 6 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Temperature Monitor (2021-2030) ($MN)
  • Table 7 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Respiratory Monitor (2021-2030) ($MN)
  • Table 8 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Blood Pressure Monitor (2021-2030) ($MN)
  • Table 9 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Heart Rate Monitor (2021-2030) ($MN)
  • Table 10 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Special Monitors (2021-2030) ($MN)
  • Table 11 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Blood Glucose Monitor (2021-2030) ($MN)
  • Table 12 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Multi-Parameter Monitors (2021-2030) ($MN)
  • Table 13 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Prothrombin Monitors (2021-2030) ($MN)
  • Table 14 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Cardiac Rhythm Monitor (2021-2030) ($MN)
  • Table 15 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Fetal Heart Rate Monitor (2021-2030) ($MN)
  • Table 16 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Anaesthesia Monitors (2021-2030) ($MN)
  • Table 17 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Other Products (2021-2030) ($MN)
  • Table 18 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Solution (2021-2030) ($MN)
  • Table 19 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Software (2021-2030) ($MN)
  • Table 20 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Hardware (2021-2030) ($MN)
  • Table 21 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Services (2021-2030) ($MN)
  • Table 22 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Technology (2021-2030) ($MN)
  • Table 23 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Natural Language Processing (2021-2030) ($MN)
  • Table 24 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Machine Learning (2021-2030) ($MN)
  • Table 25 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Querying Method (2021-2030) ($MN)
  • Table 26 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Speech Recognition (2021-2030) ($MN)
  • Table 27 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Application (2021-2030) ($MN)
  • Table 28 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Diabetes (2021-2030) ($MN)
  • Table 29 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Respiratory Issues (2021-2030) ($MN)
  • Table 30 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Weight Management & Fitness Monitoring (2021-2030) ($MN)
  • Table 31 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Cancer (2021-2030) ($MN)
  • Table 32 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Dehydration (2021-2030) ($MN)
  • Table 33 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Cardiovascular Diseases (2021-2030) ($MN)
  • Table 34 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Sleep Disorder (2021-2030) ($MN)
  • Table 35 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Viral Infection (2021-2030) ($MN)
  • Table 36 Global Artificial Intelligence In Remote Patient Monitoring Market Outlook, By Other Applications (2021-2030) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.