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1865534

全球腫瘤人工智慧市場：預測至 2032 年—按組件、癌症類型、技術、應用、最終用戶和地區分類的分析

AI in Oncology Market Forecasts to 2032 - Global Analysis By Component (Software Solutions, Hardware and Services), Cancer Type, Technology, Application, End User 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 的一項研究，預計到 2025 年，全球腫瘤人工智慧市場價值將達到 32 億美元，到 2032 年預計將達到 217 億美元。

預計在預測期內，腫瘤人工智慧（AI）將以31.4%的複合年成長率成長。腫瘤人工智慧是指利用先進的計算演算法和機器學習模型來增強癌症的檢測、診斷、治療方案製定和病患監測。透過分析包括醫學影像、基因組圖譜和臨床記錄在內的大型複雜資料集，人工智慧系統能夠識別更細微的模式，並比傳統方法更準確地預測疾病進展。在腫瘤學領域，人工智慧有助於早期腫瘤檢測、個人化治療方法選擇和藥物研發，有助於提高整體治療效果。它還能幫助放射科醫生和腫瘤科醫生做出數據驅動的臨床決策，最終促進精準醫療和以患者為中心的癌症治療的發展。

腫瘤數據可用性的不斷提高

臨床記錄、基因組圖譜和影像資料集正在醫院、研究中心和生物樣本庫中迅速擴展。平台利用結構化和非結構化資料來訓練模型，用於早期檢測、風險分層和治療方案選擇。與電子健康記錄(EHR)、病理系統和放射影像檔案的整合提高了模型的準確性和臨床效用。精準腫瘤學和人群健康管理計劃對可擴展、數據豐富的平台的需求日益成長。這些趨勢正在推動人工智慧驅動的癌症治療生態系統中平台的普及應用。

高成本

企業在將舊有系統與人工智慧引擎連接並確保臨床工作流程的互通性方面面臨諸多挑戰。基礎設施升級、數據協調和人員培訓增加了實施的複雜性和成本。缺乏標準化的通訊協定和報銷框架進一步阻礙了醫院和研究機構的採用。供應商必須提供模組化解決方案、雲端原生架構和整合支援才能克服這些障礙。在資源有限且對合規性要求嚴格的環境中，這些限制持續阻礙著平台的成熟。

個人化醫療和治療最佳化

這些模型基於患者特異性數據，用於預測腫瘤反應、識別生物標記並指導治療方法的選擇。與基因組定序、免疫分析和臨床試驗的整合可提高預測的準確性並追蹤治療結果。在乳癌、肺癌和大腸癌計畫中，對適應性強且可解釋的人工智慧的需求日益成長。各公司正在將其人工智慧策略與基於價值的醫療、臨床決策支援和藥物研發目標相契合。這些趨勢正在推動個人化醫療和以結果為導向的腫瘤學平台的發展。

隱私、安全和倫理問題

敏感的患者數據、基因組資訊和治療記錄需要強大的加密、知情同意管理和審核。企業在遵守 HIPAA、GDPR 和當地資料保護法律的同時，也要維持模型效能，這面臨許多挑戰。缺乏透明度、演算法偏差和課責不明確會削弱相關人員的信任，並阻礙臨床應用。供應商必須透過投資管治儀表板、倫理人工智慧框架和相關人員參與來應對這些風險。這些限制因素持續阻礙平台在受監管的高風險腫瘤學領域的應用。

新冠疫情的影響：

疫情擾亂了全球醫療系統的癌症篩檢、臨床試驗和腫瘤診療流程。封鎖措施延誤了診斷和治療，同時增加了對遠端監測和數位化決策支援的需求。人工智慧平台迅速擴展，為遠距腫瘤診療計畫中的分流、虛擬腫瘤諮詢和影像分析提供支援。公共和私營部門對雲端基礎設施、即時分析和分散式臨床試驗的投資激增。政策制定者和消費者群體對癌症風險和數位健康工具的認知度也隨之提高。

預計在預測期內，機器學習領域將佔據最大的市場規模。

由於機器學習在腫瘤學工作流程中展現的多功能性、擴充性和卓越性能，預計在預測期內，機器學習領域將佔據最大的市場佔有率。模型採用監督式學習和非監督式學習技術，支援影像分類、風險預測和治療建議。與放射組學、基因組學和臨床數據的整合，提高了模型在不同癌症類型中的準確性和適用性。在診斷、藥物研發和臨床決策支援領域，對自適應和可解釋機器學習的需求日益成長。供應商提供模組化引擎、API 和視覺化工具，以促進跨職能部門的應用和效能追蹤。

預計在預測期內，肺癌細分市場將實現最高的複合年成長率。

預計在預測期內，肺癌領域將迎來最高的成長率，因為人工智慧平台正擴展到早期檢測、分期和治療最佳化等多個方面。模型分析電腦斷層掃描、病理標本和分子數據，以識別結節、預測疾病進展並指南免疫療法。與篩檢項目、臨床試驗和真實世界數據的整合，能夠提升其影響力和擴充性。公共衛生、腫瘤學和藥物研發領域對擴充性且高度精準的解決方案的需求日益成長。供應商提供基於人工智慧的圖像分析工具、生物標記發現引擎以及專為肺癌工作流程量身定做的決策支援模組。

佔比最大的地區：

由於北美在腫瘤人工智慧領域的研究基礎設施、臨床應用和監管準備方面取得的進步，預計北美將在預測期內佔據最大的市場佔有率。各公司正在醫院、癌症中心和製藥公司部署平台，以增強診斷和治療方案的發展。對雲端遷移、資料管治和人才培養的投資正在支持擴充性和合規性。主要供應商、學術機構和政策框架的存在正在推動生態系統的成熟和創新。各公司正在調整其人工智慧策略，使其與FDA指南、支付模式和精準醫療舉措保持一致。

年複合成長率最高的地區：

預計亞太地區在預測期內將實現最高的複合年成長率，這主要得益於癌症負擔加重、醫療數位化以及人工智慧投資在區域經濟體中的整合。中國、印度、日本和韓國等國家正在拓展其在篩檢、研究和臨床腫瘤學計畫方面的平台。政府支持的舉措正在推動基礎建設、Start-Ups孵化以及公私合營在癌症創新領域的應用。本地醫療機構正在提供經濟高效、符合當地文化且以行動端為先的解決方案，以滿足區域需求。都市區居民對擴充性且整體性的腫瘤學基礎設施的需求日益成長。

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訂閱本報告的用戶可從以下免費自訂選項中選擇一項：

  • 公司簡介
    • 對最多三家其他公司進行全面分析
    • 對主要企業進行SWOT分析（最多3家公司）
  • 區域分類
    • 根據客戶興趣對主要國家進行市場估算、預測和複合年成長率分析（註：基於可行性檢查）
  • 競爭基準化分析
    • 基於產品系列、地域覆蓋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 引言

  • 概述
  • 相關利益者
  • 分析範圍
  • 分析方法
    • 資料探勘
    • 數據分析
    • 數據檢驗
    • 分析方法
  • 分析材料
    • 原始研究資料
    • 二手研究資訊來源
    • 先決條件

第3章 市場趨勢分析

  • 介紹
  • 促進要素
  • 抑制因素
  • 市場機遇
  • 威脅
  • 技術分析
  • 應用分析
  • 終端用戶分析
  • 新興市場
  • 新冠疫情的感染疾病

第4章 波特五力分析

  • 供應商的議價能力
  • 買方議價能力
  • 替代產品的威脅
  • 新參與企業的威脅
  • 公司間的競爭

5. 全球腫瘤人工智慧市場（按組件分類）

  • 介紹
  • 軟體解決方案
  • 硬體
  • 服務

6. 全球腫瘤人工智慧市場（以癌症類型分類）

  • 介紹
  • 乳癌
  • 肺癌
  • 攝護腺癌
  • 大腸直腸癌
  • 子宮頸癌
  • 其他類型的癌症

7. 全球腫瘤人工智慧市場（依技術分類）

  • 介紹
  • 機器學習
  • 深度學習
  • 自然語言處理
  • 放射學和組織病理學中的電腦視覺
  • 人工智慧驅動的基因組分析和生物標記發現
  • 其他技術

8. 全球腫瘤人工智慧市場（按應用分類）

  • 介紹
  • 診斷和篩檢
  • 治療計劃和監測
  • 藥物發現與開發
  • 基因組分析
  • 預後、風險分層
  • 其他用途

9. 全球腫瘤人工智慧市場（按最終用戶分類）

  • 介紹
  • 醫院
  • 腫瘤診所
  • 研究所
  • 生物製藥和生物技術公司
  • 診斷檢查室
  • 其他最終用戶

第10章 全球腫瘤人工智慧市場（按地區分類）

  • 介紹
  • 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
  • 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
    • 其他中東和非洲地區

第11章：主要趨勢

  • 合約、商業夥伴關係和合資企業
  • 企業合併（M&A）
  • 新產品發布
  • 業務拓展
  • 其他關鍵策略

第12章：公司簡介

  • Siemens Healthineers AG
  • GE HealthCare Technologies Inc.
  • Medtronic plc
  • IBM Corporation
  • Google LLC
  • Microsoft Corporation
  • NVIDIA Corporation
  • Azra AI Inc.
  • ConcertAI LLC
  • PathAI Inc.
  • Median Technologies SA
  • Tempus Labs Inc.
  • Owkin Inc.
  • Freenome Holdings Inc.
  • Paige.AI Inc.
Product Code: SMRC32188

According to Stratistics MRC, the Global AI in Oncology Market is accounted for $3.2 billion in 2025 and is expected to reach $21.7 billion by 2032 growing at a CAGR of 31.4% during the forecast period. Artificial Intelligence (AI) in oncology refers to the use of advanced computational algorithms and machine learning models to enhance cancer detection, diagnosis, treatment planning, and patient monitoring. By analyzing large and complex datasets such as medical images, genomic profiles, and clinical records, AI systems can identify subtle patterns and predict disease progression more accurately than traditional methods. In oncology, AI aids in early tumor detection, personalized therapy selection, and drug discovery, improving overall treatment outcomes. It also supports radiologists and oncologists in making data-driven clinical decisions, ultimately advancing precision medicine and patient-centered cancer care.

Market Dynamics:

Driver:

Growing oncology data availability

Clinical records genomic profiles and imaging datasets are expanding rapidly across hospitals research centers and biobanks. Platforms use structured and unstructured data to train models for early detection risk stratification and therapy selection. Integration with EHRs pathology systems and radiology archives enhances model accuracy and clinical relevance. Demand for scalable and data-rich platforms is rising across precision oncology and population health initiatives. These dynamics are propelling platform deployment across AI-enabled cancer care ecosystems.

Restraint:

High cost of implementation and integration

Enterprises face challenges in aligning legacy systems with AI engines and ensuring interoperability across clinical workflows. Infrastructure upgrades data harmonization and staff training add complexity and cost to deployment. Lack of standardized protocols and reimbursement frameworks further delays adoption across hospitals and research institutions. Vendors must offer modular solutions cloud-native architecture and integration support to overcome these barriers. These constraints continue to hinder platform maturity across resource-constrained and compliance-sensitive environments.

Opportunity:

Personalized medicine and treatment optimization

Models predict tumor response identify biomarkers and guide therapy selection based on patient-specific data. Integration with genomic sequencing immunoprofiling and clinical trials enhances precision and outcome tracking. Demand for adaptive and explainable AI is rising across breast lung and colorectal cancer programs. Enterprises align AI strategies with value-based care clinical decision support and drug development goals. These trends are fostering growth across personalized and outcome-driven oncology platforms.

Threat:

Privacy, security and ethical concerns

Sensitive patient data genomic information and treatment records require robust encryption consent management and auditability. Enterprises face challenges in meeting HIPAA GDPR and regional data protection laws while maintaining model performance. Lack of transparency algorithmic bias and unclear accountability degrade stakeholder confidence and clinical adoption. Vendors must invest in governance dashboards ethical AI frameworks and stakeholder engagement to address these risks. These limitations continue to constrain platform deployment across regulated and high-stakes oncology environments.

Covid-19 Impact:

The pandemic disrupted cancer screening clinical trials and oncology workflows across global healthcare systems. Lockdowns delayed diagnosis and treatment while increasing demand for remote monitoring and digital decision support. AI platforms scaled rapidly to support triage virtual tumor boards and imaging analysis across teleoncology programs. Investment in cloud infrastructure real-time analytics and decentralized trials surged across public and private sectors. Public awareness of cancer risk and digital health tools increased across policy and consumer circles.

The machine learning segment is expected to be the largest during the forecast period

The machine learning segment is expected to account for the largest market share during the forecast period due to its versatility scalability and performance across oncology workflows. Models support image classification risk prediction and treatment recommendation using supervised and unsupervised learning techniques. Integration with radiomics genomics and clinical data enhances accuracy and generalizability across cancer types. Demand for adaptive and explainable ML is rising across diagnostics drug discovery and clinical decision support. Vendors offer modular engines APIs and visualization tools to support cross-functional adoption and performance tracking.

The lung cancer segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the lung cancer segment is predicted to witness the highest growth rate as AI platforms expand across early detection staging and therapy optimization. Models analyze CT scans pathology slides and molecular data to identify nodules predict progression and guide immunotherapy. Integration with screening programs clinical trials and real-world evidence enhances impact and scalability. Demand for scalable and high-accuracy solutions is rising across public health oncology and pharmaceutical research. Vendors offer AI-powered imaging tools biomarker discovery engines and decision support modules tailored to lung cancer workflows.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share due to its research infrastructure clinical adoption and regulatory engagement across AI in oncology. Enterprises deploy platforms across hospitals cancer centers and pharmaceutical firms to enhance diagnostics and treatment planning. Investment in cloud migration data governance and workforce development supports scalability and compliance. Presence of leading vendors academic institutions and policy frameworks drives ecosystem maturity and innovation. Firms align AI strategies with FDA guidance payer models and precision medicine initiatives.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR as cancer burden healthcare digitization and AI investment converge across regional economies. Countries like China India Japan and South Korea scale platforms across screening research and clinical oncology programs. Government-backed initiatives support infrastructure development startup incubation and public-private partnerships across cancer innovation. Local providers offer cost-effective culturally adapted and mobile-first solutions tailored to regional needs. Demand for scalable and inclusive oncology infrastructure is rising across urban and rural populations.

Key players in the market

Some of the key players in AI in Oncology Market include Siemens Healthineers AG, GE HealthCare Technologies Inc., Medtronic plc, IBM Corporation, Google LLC, Microsoft Corporation, NVIDIA Corporation, Azra AI Inc., ConcertAI LLC, PathAI Inc., Median Technologies SA, Tempus Labs Inc., Owkin Inc., Freenome Holdings Inc. and Paige.AI Inc.

Key Developments:

In July 2025, Siemens Healthineers signed a $50 million value partnership with Prisma Health, South Carolina's largest hospital system. The agreement expanded their 10-year collaboration to include AI-powered oncology solutions, notably the deployment of the Ethos radiotherapy system from Varian. The system enables adaptive therapy planning using real-time imaging and artificial intelligence.

In July 2024, GE HealthCare signed an agreement to acquire Intelligent Ultrasound Group PLC's clinical AI software business for approximately $51 million. The acquisition added real-time image recognition capabilities to GE's ultrasound portfolio, supporting oncology diagnostics in OBGYN and abdominal imaging. It aligned with GE's precision care strategy to improve exam accuracy and efficiency.

Components Covered:

  • Software Solutions
  • Hardware
  • Services

Cancer Types Covered:

  • Breast Cancer
  • Lung Cancer
  • Prostate Cancer
  • Colorectal Cancer
  • Cervical Cancer
  • Other Cancer Types

Technologies Covered:

  • Machine Learning
  • Deep Learning
  • Natural Language Processing
  • Computer Vision for Radiomics and Histopathology
  • AI-Driven Genomic Profiling and Biomarker Discovery
  • Other Technologies

Applications Covered:

  • Diagnosis & Screening
  • Treatment Planning & Monitoring
  • Drug Discovery & Development
  • Genomic Profiling
  • Prognostics & Risk Stratification
  • Other Applications

End Users Covered:

  • Hospitals
  • Oncology Clinics
  • Research Institutes
  • Biopharmaceutical & Biotechnology Companies
  • Diagnostic Laboratories
  • Other End Users

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 2024, 2025, 2026, 2028, and 2032
  • 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 Technology Analysis
  • 3.7 Application Analysis
  • 3.8 End User 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 AI in Oncology Market, By Component

  • 5.1 Introduction
  • 5.2 Software Solutions
  • 5.3 Hardware
  • 5.4 Services

6 Global AI in Oncology Market, By Cancer Type

  • 6.1 Introduction
  • 6.2 Breast Cancer
  • 6.3 Lung Cancer
  • 6.4 Prostate Cancer
  • 6.5 Colorectal Cancer
  • 6.6 Cervical Cancer
  • 6.7 Other Cancer Types

7 Global AI in Oncology Market, By Technology

  • 7.1 Introduction
  • 7.2 Machine Learning
  • 7.3 Deep Learning
  • 7.4 Natural Language Processing
  • 7.5 Computer Vision for Radiomics and Histopathology
  • 7.6 AI-Driven Genomic Profiling and Biomarker Discovery
  • 7.7 Other Technologies

8 Global AI in Oncology Market, By Application

  • 8.1 Introduction
  • 8.2 Diagnosis & Screening
  • 8.3 Treatment Planning & Monitoring
  • 8.4 Drug Discovery & Development
  • 8.5 Genomic Profiling
  • 8.6 Prognostics & Risk Stratification
  • 8.7 Other Applications

9 Global AI in Oncology Market, By End User

  • 9.1 Introduction
  • 9.2 Hospitals
  • 9.3 Oncology Clinics
  • 9.4 Research Institutes
  • 9.5 Biopharmaceutical & Biotechnology Companies
  • 9.6 Diagnostic Laboratories
  • 9.7 Other End Users

10 Global AI in Oncology Market, By Geography

  • 10.1 Introduction
  • 10.2 North America
    • 10.2.1 US
    • 10.2.2 Canada
    • 10.2.3 Mexico
  • 10.3 Europe
    • 10.3.1 Germany
    • 10.3.2 UK
    • 10.3.3 Italy
    • 10.3.4 France
    • 10.3.5 Spain
    • 10.3.6 Rest of Europe
  • 10.4 Asia Pacific
    • 10.4.1 Japan
    • 10.4.2 China
    • 10.4.3 India
    • 10.4.4 Australia
    • 10.4.5 New Zealand
    • 10.4.6 South Korea
    • 10.4.7 Rest of Asia Pacific
  • 10.5 South America
    • 10.5.1 Argentina
    • 10.5.2 Brazil
    • 10.5.3 Chile
    • 10.5.4 Rest of South America
  • 10.6 Middle East & Africa
    • 10.6.1 Saudi Arabia
    • 10.6.2 UAE
    • 10.6.3 Qatar
    • 10.6.4 South Africa
    • 10.6.5 Rest of Middle East & Africa

11 Key Developments

  • 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 11.2 Acquisitions & Mergers
  • 11.3 New Product Launch
  • 11.4 Expansions
  • 11.5 Other Key Strategies

12 Company Profiling

  • 12.1 Siemens Healthineers AG
  • 12.2 GE HealthCare Technologies Inc.
  • 12.3 Medtronic plc
  • 12.4 IBM Corporation
  • 12.5 Google LLC
  • 12.6 Microsoft Corporation
  • 12.7 NVIDIA Corporation
  • 12.8 Azra AI Inc.
  • 12.9 ConcertAI LLC
  • 12.10 PathAI Inc.
  • 12.11 Median Technologies SA
  • 12.12 Tempus Labs Inc.
  • 12.13 Owkin Inc.
  • 12.14 Freenome Holdings Inc.
  • 12.15 Paige.AI Inc.

List of Tables

  • Table 1 Global AI in Oncology Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global AI in Oncology Market Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global AI in Oncology Market Outlook, By Software Solutions (2024-2032) ($MN)
  • Table 4 Global AI in Oncology Market Outlook, By Hardware (2024-2032) ($MN)
  • Table 5 Global AI in Oncology Market Outlook, By Services (2024-2032) ($MN)
  • Table 6 Global AI in Oncology Market Outlook, By Cancer Type (2024-2032) ($MN)
  • Table 7 Global AI in Oncology Market Outlook, By Breast Cancer (2024-2032) ($MN)
  • Table 8 Global AI in Oncology Market Outlook, By Lung Cancer (2024-2032) ($MN)
  • Table 9 Global AI in Oncology Market Outlook, By Prostate Cancer (2024-2032) ($MN)
  • Table 10 Global AI in Oncology Market Outlook, By Colorectal Cancer (2024-2032) ($MN)
  • Table 11 Global AI in Oncology Market Outlook, By Cervical Cancer (2024-2032) ($MN)
  • Table 12 Global AI in Oncology Market Outlook, By Other Cancer Types (2024-2032) ($MN)
  • Table 13 Global AI in Oncology Market Outlook, By Technology (2024-2032) ($MN)
  • Table 14 Global AI in Oncology Market Outlook, By Machine Learning (2024-2032) ($MN)
  • Table 15 Global AI in Oncology Market Outlook, By Deep Learning (2024-2032) ($MN)
  • Table 16 Global AI in Oncology Market Outlook, By Natural Language Processing (2024-2032) ($MN)
  • Table 17 Global AI in Oncology Market Outlook, By Computer Vision for Radiomics and Histopathology (2024-2032) ($MN)
  • Table 18 Global AI in Oncology Market Outlook, By AI-Driven Genomic Profiling and Biomarker Discovery (2024-2032) ($MN)
  • Table 19 Global AI in Oncology Market Outlook, By Other Technologies (2024-2032) ($MN)
  • Table 20 Global AI in Oncology Market Outlook, By Application (2024-2032) ($MN)
  • Table 21 Global AI in Oncology Market Outlook, By Diagnosis & Screening (2024-2032) ($MN)
  • Table 22 Global AI in Oncology Market Outlook, By Treatment Planning & Monitoring (2024-2032) ($MN)
  • Table 23 Global AI in Oncology Market Outlook, By Drug Discovery & Development (2024-2032) ($MN)
  • Table 24 Global AI in Oncology Market Outlook, By Genomic Profiling (2024-2032) ($MN)
  • Table 25 Global AI in Oncology Market Outlook, By Prognostics & Risk Stratification (2024-2032) ($MN)
  • Table 26 Global AI in Oncology Market Outlook, By Other Applications (2024-2032) ($MN)
  • Table 27 Global AI in Oncology Market Outlook, By End User (2024-2032) ($MN)
  • Table 28 Global AI in Oncology Market Outlook, By Hospitals (2024-2032) ($MN)
  • Table 29 Global AI in Oncology Market Outlook, By Oncology Clinics (2024-2032) ($MN)
  • Table 30 Global AI in Oncology Market Outlook, By Research Institutes (2024-2032) ($MN)
  • Table 31 Global AI in Oncology Market Outlook, By Biopharmaceutical & Biotechnology Companies (2024-2032) ($MN)
  • Table 32 Global AI in Oncology Market Outlook, By Diagnostic Laboratories (2024-2032) ($MN)
  • Table 33 Global AI in Oncology Market Outlook, By Other End Users (2024-2032) ($MN)

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