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市场调查报告书
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1865534

全球肿瘤人工智慧市场：预测至 2032 年—按组件、癌症类型、技术、应用、最终用户和地区分類的分析

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个工作天内

价格

根据 Stratistics MRC 的一项研究，预计到 2025 年，全球肿瘤人工智慧市场价值将达到 32 亿美元，到 2032 年预计将达到 217 亿美元。

预计在预测期内，肿瘤人工智慧（AI）将以31.4%的复合年增长率成长。肿瘤人工智慧是指利用先进的计算演算法和机器学习模型来增强癌症的检测、诊断、治疗方案製定和病患监测。透过分析包括医学影像、基因组图谱和临床记录在内的大型复杂资料集，人工智慧系统能够识别更细微的模式，并比传统方法更准确地预测疾病进展。在肿瘤学领域，人工智慧有助于早期肿瘤检测、个人化治疗方法选择和药物研发，有助于提高整体治疗效果。它还能帮助放射科医生和肿瘤科医生做出数据驱动的临床决策，最终促进精准医疗和以患者为中心的癌症治疗的发展。

肿瘤数据可用性的不断提高

临床记录、基因组图谱和影像资料集正在医院、研究中心和生物样本库中迅速扩展。平台利用结构化和非结构化资料来训练模型，用于早期检测、风险分层和治疗方案选择。与电子健康记录(EHR)、病理系统和放射影像檔案的整合提高了模型的准确性和临床效用。精准肿瘤学和人群健康管理计划对可扩展、数据丰富的平台的需求日益增长。这些趋势正在推动人工智慧驱动的癌症治疗生态系统中平台的普及应用。

高成本

企业在将旧有系统与人工智慧引擎连接并确保临床工作流程的互通性方面面临诸多挑战。基础设施升级、数据协调和人员培训增加了实施的复杂性和成本。缺乏标准化的通讯协定和报销框架进一步阻碍了医院和研究机构的采用。供应商必须提供模组化解决方案、云端原生架构和整合支援才能克服这些障碍。在资源有限且对合规性要求严格的环境中，这些限制持续阻碍着平台的成熟。

个人化医疗和治疗优化

这些模型基于患者特异性数据，用于预测肿瘤反应、识别生物标记并指导治疗方法的选择。与基因组定序、免疫分析和临床试验的整合可提高预测的准确性并追踪治疗结果。在乳癌、肺癌和大肠癌计画中，对适应性强且可解释的人工智慧的需求日益增长。各公司正在将其人工智慧策略与基于价值的医疗、临床决策支援和药物研发目标相契合。这些趋势正在推动个人化医疗和以结果为导向的肿瘤学平台的发展。

隐私、安全和伦理问题

敏感的患者数据、基因组资讯和治疗记录需要强大的加密、知情同意管理和审核。企业在遵守 HIPAA、GDPR 和当地资料保护法律的同时，也要维持模型效能，这面临许多挑战。缺乏透明度、演算法偏差和课责不明确会削弱相关人员的信任，并阻碍临床应用。供应商必须透过投资管治仪表板、伦理人工智慧框架和相关人员参与来应对这些风险。这些限制因素持续阻碍平台在受监管的高风险肿瘤学领域的应用。

新冠疫情的影响：

疫情扰乱了全球医疗系统的癌症筛检、临床试验和肿瘤诊疗流程。封锁措施延误了诊断和治疗，同时增加了对远端监测和数位化决策支援的需求。人工智慧平台迅速扩展，为远距肿瘤诊疗计画中的分流、虚拟肿瘤咨询和影像分析提供支援。公共和私营部门对云端基础设施、即时分析和分散式临床试验的投资激增。政策制定者和消费者群体对癌症风险和数位健康工具的认知度也随之提高。

预计在预测期内，机器学习领域将占据最大的市场规模。

由于机器学习在肿瘤学工作流程中展现的多功能性、扩充性和卓越性能，预计在预测期内，机器学习领域将占据最大的市场份额。模型采用监督式学习和非监督式学习技术，支援影像分类、风险预测和治疗建议。与放射组学、基因组学和临床数据的整合，提高了模型在不同癌症类型中的准确性和适用性。在诊断、药物研发和临床决策支援领域，对自适应和可解释机器学习的需求日益增长。供应商提供模组化引擎、API 和视觉化工具，以促进跨职能部门的应用和效能追踪。

预计在预测期内，肺癌细分市场将实现最高的复合年增长率。

预计在预测期内，肺癌领域将迎来最高的成长率，因为人工智慧平台正扩展到早期检测、分期和治疗优化等多个方面。模型分析电脑断层扫描、病理标本和分子数据，以识别结节、预测疾病进展并指南免疫疗法。与筛检项目、临床试验和真实世界数据的整合，能够提升其影响力和扩充性。公共卫生、肿瘤学和药物研发领域对扩充性且高度精准的解决方案的需求日益增长。供应商提供基于人工智慧的图像分析工具、生物标记发现引擎以及专为肺癌工作流程量身定制的决策支援模组。

占比最大的地区：

由于北美在肿瘤人工智慧领域的研究基础设施、临床应用和监管准备方面取得的进步，预计北美将在预测期内占据最大的市场份额。各公司正在医院、癌症中心和製药公司部署平台，以增强诊断和治疗方案的发展。对云端迁移、资料管治和人才培养的投资正在支持扩充性和合规性。主要供应商、学术机构和政策框架的存在正在推动生态系统的成熟和创新。各公司正在调整其人工智慧策略，使其与FDA指南、支付模式和精准医疗倡议保持一致。

年复合成长率最高的地区：

预计亚太地区在预测期内将实现最高的复合年增长率，这主要得益于癌症负担加重、医疗数位化以及人工智慧投资在区域经济体中的整合。中国、印度、日本和韩国等国家正在拓展其在筛检、研究和临床肿瘤学计画方面的平台。政府支持的倡议正在推动基础建设、Start-Ups孵化以及公私合营在癌症创新领域的应用。本地医疗机构正在提供经济高效、符合当地文化且以行动端为先的解决方案，以满足区域需求。都市区居民对扩充性且整体性的肿瘤学基础设施的需求日益增长。

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  • 公司简介
    • 对最多三家其他公司进行全面分析
    • 对主要企业进行SWOT分析（最多3家公司）
  • 区域分类
    • 根据客户兴趣对主要国家进行市场估算、预测和复合年增长率分析（註：基于可行性检查）
  • 竞争基准化分析
    • 基于产品系列、地域覆盖和策略联盟对主要企业基准化分析

目录

第一章执行摘要

第二章 引言

  • 概述
  • 相关利益者
  • 分析范围
  • 分析方法
    • 资料探勘
    • 数据分析
    • 数据检验
    • 分析方法
  • 分析材料
    • 原始研究资料
    • 二手研究资讯来源
    • 先决条件

第三章 市场趋势分析

  • 介绍
  • 司机
  • 抑制因素
  • 市场机会
  • 威胁
  • 技术分析
  • 应用分析
  • 终端用户分析
  • 新兴市场
  • 新冠疫情的感染疾病

第四章 波特五力分析

  • 供应商的议价能力
  • 买方议价能力
  • 替代产品的威胁
  • 新参与企业的威胁
  • 公司间的竞争

5. 全球肿瘤人工智慧市场（按组件划分）

  • 介绍
  • 软体解决方案
  • 硬体
  • 服务

6. 全球肿瘤人工智慧市场（以癌症类型划分）

  • 介绍
  • 乳癌
  • 肺癌
  • 摄护腺癌
  • 大肠直肠癌
  • 子宫颈癌
  • 其他类型的癌症

7. 全球肿瘤人工智慧市场（依技术划分）

  • 介绍
  • 机器学习
  • 深度学习
  • 自然语言处理
  • 放射学和组织病理学中的电脑视觉
  • 人工智慧驱动的基因组分析和生物标记发现
  • 其他技术

8. 全球肿瘤人工智慧市场（按应用划分）

  • 介绍
  • 诊断和筛检
  • 治疗计划和监测
  • 药物发现与开发
  • 基因组分析
  • 预后、风险分层
  • 其他用途

9. 全球肿瘤人工智慧市场（按最终用户划分）

  • 介绍
  • 医院
  • 肿瘤诊所
  • 研究所
  • 生物製药和生物技术公司
  • 诊断检查室
  • 其他最终用户

第十章 全球肿瘤人工智慧市场（按地区划分）

  • 介绍
  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 其他亚太地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地区
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲地区

第十一章：主要趋势

  • 合约、商业伙伴关係和合资企业
  • 企业合併（M&A）
  • 新产品发布
  • 业务拓展
  • 其他关键策略

第十二章：公司简介

  • 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.