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癌症治疗领域人工智慧 (AI) 市场——产业趋势及全球预测（至 2040 年）——按癌症类型、最终用户和地区划分

AI In Oncology Market, till 2040: Distribution by Type of Cancer, Type of End User, and Geographical Regions: Industry Trends and Global Forecasts
出版日期: | 出版商: Roots Analysis | 英文 165 Pages | 商品交期: 最快1-2个工作天内

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简介目录

癌症治疗领域人工智慧市场展望

全球癌症治疗领域人工智慧市场预计将从目前的 27 亿美元增长至 2040 年的 173 亿美元，在预测期内（至 2040 年）的复合年增长率 (CAGR) 为 14.1%。本研究提供有关市场规模、成长情境、产业趋势和未来预测的资讯。

全球癌症发生率的不断上升推动了对先进诊断和治疗方法的需求。人工智慧 (AI) 正在改变肿瘤学，从早期检测、影像和病理分析（例如乳房 X 光检查和 CT 扫描）到个人化治疗，人工智慧在患者治疗的各个阶段都能改善癌症护理。它还有助于预测患者预后，从而提高医疗服务的效率、准确性和可近性。

预计在预测期内，肿瘤领域的人工智慧市场将以显着的速度成长。这主要得益于对早期精准检测的迫切需求、精准医疗的兴起，以及为应对日益增长的全球癌症负担而需要优化且经济有效的治疗方案。

肿瘤领域人工智慧市场-IMG1

高阶主管策略洞察

肿瘤领域人工智慧市场：竞争格局

肿瘤领域人工智慧市场的竞争格局呈现出来自大型企业和小型企业的激烈竞争。西门子医疗和通用电气医疗透过将各种成像设备与 70 多种 FDA 批准的 AI 演算法相结合，建立了市场主导地位，从而创造了持续的软体收入并确保了工作流程的整合。此外，IBM、NVIDIA、PathAI、ConcertAI、Tempus、Oracle、美敦力、飞利浦等主要厂商，以及 Azra AI 和 Paige AI 等新兴公司，都在诊断、药物研发、病理学和精准医疗领域提供专业解决方案。

人工智慧在癌症治疗领域有哪些机会？

预计到 2040 年，全球癌症治疗领域的人工智慧市场规模将达到 173 亿美元。目前，实体瘤在癌症类型中占据了大部分市场份额。

全球癌症发生率的上升以及对创新人工智慧驱动的早期检测工具日益增长的需求，凸显了人工智慧在癌症治疗领域的重要作用。此外，人工智慧在肿瘤学和分子生物学领域个性化治疗的日益广泛应用，预计将在整个预测期内推动市场扩张。

人工智慧在癌症治疗领域的演进：新兴产业趋势

肿瘤学领域人工智慧 (AI) 的新兴趋势强调精准诊断、个人化治疗和加速药物研发流程。人工智慧驱动的演算法透过先进的影像技术（例如 PET/CT 融合成像和组织病理学分析）显着提高了早期癌症的检测率，肿瘤检测准确率高达 99%。在治疗决策方面，人工智慧利用多组学资料集、基因组分析和全面的患者记录来预测治疗反应并模拟肿瘤微环境，从而指导精准干预。此外，人工智慧还透过先进的平台优化临床试验参与者的招募，促进奈米载体工程，并利用奈米感测器实现即时监测。

推动癌症治疗领域人工智慧市场成长的关键因素

推动癌症治疗领域人工智慧市场成长的关键因素有几个。全球癌症发生率的不断攀升推动了对先进诊断解决方案的需求，而人工智慧增强的成像和分析技术能够实现超越人类能力的早期精准肿瘤检测。此外，製药和生物技术产业的巨额投资正透过预测建模加速药物研发进程，从而降低临床试验的成本和时间。同时，FDA 等监管机构的批准、资金的增加以及医疗机构的广泛应用，也使得人工智慧在诊断、治疗方案製定和营运效率提升方面得以实际应用。

主要市场挑战

肿瘤学领域的人工智慧市场面临着许多挑战，包括难以取得大型、高品质且具代表性的多模态资料集，这会影响模型的效能。资料收集、基础设施建设以及与现有肿瘤工作流程整合的高昂前期成本，以及与传统 IT 系统缺乏互通性，都限制了人工智慧的应用，尤其是在规模较小或资源有限的医疗机构中。此外，监管架构尚不明确且不断演变，加之对敏感基因组和肿瘤资料安全保护的需求日益增长，都在减缓人工智慧解决方案在实际​​肿瘤治疗中的审批和推广。

肿瘤人工智慧市场：主要市场区隔

癌症类型

  • 实体恶性肿瘤
  • 乳癌
  • 肺癌
  • 前列腺癌
  • 大肠直肠癌
  • 脑肿瘤
  • 其他

最终使用者类型

  • 医院
  • 製药公司
  • 研究机构
  • 其他

地理区域

  • 北美
  • 美国
  • 加拿大
  • 墨西哥
  • 其他北美地区国家/地区
  • 欧洲
  • 奥地利
  • 比利时
  • 丹麦
  • 法国
  • 德国
  • 爱尔兰
  • 义大利
  • 荷兰
  • 挪威
  • 俄罗斯
  • 西班牙
  • 瑞典
  • 瑞士
  • 英国
  • 其他欧洲国家/地区
  • 亚洲
  • 中国
  • 印度
  • 日本
  • 新加坡
  • 韩国
  • 其他亚洲国家/地区
  • 拉丁美洲
  • 巴西
  • 智利
  • 哥伦比亚
  • 委内瑞拉
  • 其他拉丁美洲国家/地区
  • 中东和北非非洲
  • 埃及
  • 伊朗
  • 伊拉克
  • 以色列
  • 科威特
  • 沙乌地阿拉伯
  • 阿拉伯联合大公国
  • 其他中东和北非国家
  • 世界其他地区
  • 澳大利亚
  • 纽西兰

人工智慧在癌症治疗市场：关键市场份额洞察

以癌症类型划分的市占率

依癌症类型划分，全球市场可分为实体恶性肿瘤、乳癌、肺癌、摄护腺癌、大肠癌、脑肿瘤和其他癌症。据我们估计，实体恶性肿瘤目前占据了大部分市场份额。这是由于癌症发生率不断上升，从而推动了对创新、可扩展且精准的工具的需求。

依地区划分的市占率

据我们估计，欧洲目前在肿瘤人工智慧市场中占有较大份额。这主要归功于製药公司越来越多地使用基于人工智慧的工具进行药物研发，以及旨在改善欧洲医疗保健体系的合作协议的增加。此外，值得注意的是，亚太地区的肿瘤人工智慧市场预计在预测期内将以更高的复合年增长率成长。

人工智慧癌症市场主要参与者

  • Berg（BPGbio 旗下公司）
  • CancerCenter.AI
  • Concert AI
  • GE Healthcare
  • IBM Watson Health
  • iCAD
  • JLK Inspection
  • Median Technologies
  • Path AI
  • Roche Diagnostics

人工智慧癌症市场：报告范围

本报告对人工智慧癌症市场进行了详细分析，涵盖以下几个方面：

  • 市场规模与机会分析：对人工智慧癌症市场进行详细分析，重点关注以下关键市场细分：[A] 癌症类型，[B] 最终用户类型，以及 [C] 主要地区。
  • 竞争格局：基于多个相关参数（包括成立年份、公司规模、总部所在地和所有权结构）对人工智慧癌症市场中的公司进行全面分析。
  • 公司简介：提供人工智慧癌症治疗市场主要公司的详细简介，包括以下资讯：[A] 总部所在地，[B] 公司规模，[C] 企业理念，[D] 地理位置，[E] 管理团队，[F] 联络方式，[G] 财务资讯，[H] 业务板块，[I] 技术/平台组合，以及未来 [J] 近期发展和未来。
  • 宏观趋势：评估人工智慧癌症治疗产业的当前宏观趋势。
  • 专利分析：基于相关参数（例如 [A] 专利类型，[B] 专利公开年份，[C] 专利年龄，以及 [D] 主要参与者）对与人工智慧癌症治疗相关的已申请/已授权专利进行深入分析。
  • 近期发展：概述人工智慧在癌症治疗市场的最新发展，并基于相关参数进行分析，例如[A] 启动年份、[B] 计画类型、[C] 地理分布和[D] 主要参与者。
  • 波特五力分析：分析人工智慧在肿瘤治疗市场中的五种竞争力量（新进入者的威胁、买方的议价能力、供应商的议价能力、替代品的威胁以及现有竞争对手之间的竞争）。
  • SWOT 分析：深入剖析该领域的优势、劣势、机会和威胁。此外，还提供哈维鲍尔分析，突出每个 SWOT 参数的相对影响。
  • 价值链分析：全面分析人工智慧在肿瘤治疗市场的各个阶段和利害关係人。

目录

第一章：前言

第二章：执行摘要

第三章：导论

  • 章节概述
  • 人工智慧概述
  • 人工智慧的类型
  • 人工智慧在癌症治疗中的作用
  • 人工智慧应用的关键挑战
  • 未来展望

第四章：市场概述

  • 章节概述
  • 人工智慧在癌症治疗的应用：软体供应商的市场格局
  • 人工智慧在癌症治疗中的应用：软体解决方案的市场格局

第五章：公司简介

  • 章节概述
  • 罗氏诊断
  • IBM Watson Health
  • CancerCenter.AI
  • GE Healthcare
  • Concert AI
    • Path AI
    • Berg
    • Median Technologies
    • iCAD
    • JLK Inspection

第六章：竞争分析

  • 章节概述
  • 假设和关键参数
  • 研究方法

第七章：专利分析

  • 章节概述
  • 范围与研究方法
  • 人工智慧在癌症治疗的应用：专利分析
  • 人工智慧在癌症治疗的应用：专利基准分析

第八章：合作与伙伴关係

  • 章节概述
  • 合作模式
  • 人工智慧在癌症治疗的应用：近期合作与伙伴关係合作

第九章 融资与投资分析

  • 章节概述
  • 融资模式类型
  • 人工智慧在癌症治疗的应用：融资与投资分析列表
  • 投资总结
  • 结论

第十章：蓝海策略：新创企业进入竞争激烈市场的策略指南

  • 章节概述
  • 蓝海策略概述
    • 红海
    • 蓝海
    • 红海策略与蓝海策略的差异
    • 人工智慧在癌症治疗的应用：蓝海策略与工具转型
  • 结论

第十一章 市场规模与机会分析

  • 章节概述
  • 关键资讯假设与研究方法
  • 全球肿瘤人工智慧市场
  • 癌症治疗中的人工智慧：按癌症类型分析
  • 癌症治疗中的人工智慧：按最终用户类型分析
  • 癌症治疗中的人工智慧：按主要地区分析

第十二章：结论

第十三章：高阶主管洞察

第十四章：附录 1：表格资料

第十五章：附录 2：公司与组织清单

简介目录
Product Code: RA100373

AI in Oncology Market Outlook

As per Roots Analysis, the global AI in oncology market size is estimated to grow from USD 2.7 billion in the current year to USD 17.3 billion by 2040, at a CAGR of 14.1% during the forecast period, till 2040. The new study provides information on market size, growth scenarios, industry trends and future forecasts.

Given the rising incidence of cancer globally, there has been an increased demand for advanced diagnostic and treatment methods to care for patients. Artificial Intelligence (AI) is transforming oncology by improving cancer care at every stage of the patient's journey, from early detection through imaging and pathology analysis (such as mammograms and CT scans) to personalized treatment. It also aids in predicting patient outcomes, thereby enhancing efficiency, accuracy, and accessibility of care.

AI in oncology market is expected to rise at a significant rate throughout the forecast period. This is due to urgent demand for early, accurate detection, the shift toward precision medicine, and the need for optimized, cost-effective treatment planning to manage a rising global cancer burden.

AI In Oncology Market - IMG1

Strategic Insights for Senior Leaders

AI in Oncology Market: Competitive Landscape of Companies in this Industry

The competitive landscape of AI in oncology market is characterized by intense competition, featuring a combination of large and smaller firms. Siemens Healthineers and GE Healthcare hold dominant positions through extensive imaging equipment, using >70 FDA-cleared AI algorithms to generate recurring software revenue and ensure workflow integration. Further, other key players, such as IBM, NVIDIA, PathAI, ConcertAI, Tempus, Oracle, Medtronic, and Philips, along with emerging players like Azra AI, Paige AI, offer targeted solutions in diagnostics, drug discovery, pathology, and precision medicine.

What is the Opportunity for AI in Oncology?

The global AI in oncology market is projected to reach USD 17.3 billion by 2040. Solid tumors currently dominate the market share among other cancer types.

Rising cancer prevalence worldwide, along with the need for innovative AI-driven early detection tools, highlights the critical role of AI in oncology. Additionally, expanding AI applications in oncology and molecular biology for personalized therapies are likely to fuel market expansion throughout the forecast period.

AI in Oncology Evolution: Emerging Trends in the Industry

Emerging trends in artificial intelligence (AI) within the oncology sector emphasize precision diagnostics, personalized therapies, and expedited drug development pipelines. AI-driven algorithms significantly improve early-stage cancer identification via advanced imaging modalities such as PET / CT fusion and histopathological analysis, attaining tumor detection accuracies to 99%. For therapeutic decision-making, AI leverages multi-omics datasets, genomic profiling, and comprehensive patient records to forecast treatment efficacy, and model tumor microenvironments to advance precision interventions. Further, AI optimizes clinical trial recruitment via advanced platforms, facilitates nanocarrier engineering, and enables real-time surveillance with nano sensors.

Key Drivers Propelling Growth of AI in Oncology Market

The growth of the AI in oncology market is propelled by several pivotal drivers. The escalating global incidence of cancer has heightened demand for advanced diagnostic solutions, where AI-enhanced imaging and analytics enable earlier and more accurate tumor detection beyond human capabilities. Further, substantial investments from pharmaceutical and biotechnology sectors have accelerated drug discovery processes through predictive modeling, thereby reducing clinical trial expenses and timelines. Furthermore, regulatory endorsements such as FDA approvals, coupled with increased funding and widespread adoption in healthcare institutions, have enabled the practical deployment of AI across diagnostics, treatment planning, and operational efficiencies.

Key Market Challenges

The market for AI in oncology faces significant challenges, including limited access to large, high-quality, and representative multimodal datasets which affect model performance. High upfront costs for data acquisition, infrastructure, and integration into existing oncology workflows, combined with a lack of interoperability with legacy IT systems, also limits the adoption, especially in smaller or resource-limited centers. Additionally, unclear and evolving regulatory frameworks, coupled with heightened requirements for data security and protection of sensitive genomic and oncology data, slow approvals and scale-up of AI solutions in real-world oncology practice.

AI in Oncology Market: Key Market Segmentation

Type of Cancer

  • Solid malignancies
  • Breast cancer
  • Lung cancer
  • Prostate cancer
  • Colorectal cancer
  • Brain tumor
  • Others

Type of End User

  • Hospitals
  • Pharmaceutical companies
  • Research Institutes
  • Others

Geographical Regions

  • North America
  • US
  • Canada
  • Mexico
  • Other North American countries
  • Europe
  • Austria
  • Belgium
  • Denmark
  • France
  • Germany
  • Ireland
  • Italy
  • Netherlands
  • Norway
  • Russia
  • Spain
  • Sweden
  • Switzerland
  • UK
  • Other European countries
  • Asia
  • China
  • India
  • Japan
  • Singapore
  • South Korea
  • Other Asian countries
  • Latin America
  • Brazil
  • Chile
  • Colombia
  • Venezuela
  • Other Latin American countries
  • Middle East and North Africa
  • Egypt
  • Iran
  • Iraq
  • Israel
  • Kuwait
  • Saudi Arabia
  • UAE
  • Other MENA countries
  • Rest of the World
  • Australia
  • New Zealand

AI in Oncology Market: Key Market Share Insights

Market Share by Type of Cancer

Based on the type of cancer, the global market is segmented into solid malignancies, breast cancer, lung cancer, prostate cancer, colorectal cancer, brain tumor and others. According to our estimates, currently, solid malignancies segment captures majority share of the market. This is due to the increasing prevalence of cancer, which creates the need for innovative, scalable, and precise tools.

Market Share by Geography

According to our estimates Europe currently captures a significant share of the AI in oncology market. This is due to the increasing utilization of AI-based tools by pharmaceutical companies for drug discovery and the rise in partnership agreements aimed at improving healthcare system in Europe. It is also important to note that the AI in oncology market in the Asia-Pacific region is expected to grow at a higher CAGR over the forecast period.

Example Players in AI in Oncology Market

  • Berg (A part of BPGbio)
  • CancerCenter.AI
  • Concert AI
  • GE Healthcare
  • IBM Watson Health
  • iCAD
  • JLK Inspection
  • Median Technologies
  • Path AI
  • Roche Diagnostics

AI in Oncology Market: Report Coverage

The report on the AI in oncology market features insights on various sections, including:

  • Market Sizing and Opportunity Analysis: An in-depth analysis of the AI in oncology market, focusing on key market segments, including [A] type of cancer, [B] type of end user, and [C] key geographical regions.
  • Competitive Landscape: A comprehensive analysis of the companies engaged in the AI in oncology market, based on several relevant parameters, such as [A] year of establishment, [B] company size, [C] location of headquarters and [D] ownership structure.
  • Company Profiles: Elaborate profiles of prominent players engaged in the AI in oncology market, providing details on [A] location of headquarters, [B] company size, [C] company mission, [D] company footprint, [E] management team, [F] contact details, [G] financial information, [H] operating business segments, [I] technology / platform portfolio, [J] recent developments, and an informed future outlook.
  • Megatrends: An evaluation of ongoing megatrends in the AI in oncology industry.
  • Patent Analysis: An insightful analysis of patents filed / granted in the AI in oncology domain, based on relevant parameters, including [A] type of patent, [B] patent publication year, [C] patent age and [D] leading players.
  • Recent Developments: An overview of the recent developments made in the AI in oncology market, along with analysis based on relevant parameters, including [A] year of initiative, [B] type of initiative, [C] geographical distribution and [D] most active players.
  • Porter's Five Forces Analysis: An analysis of five competitive forces prevailing in the AI in oncology market, including threats of new entrants, bargaining power of buyers, bargaining power of suppliers, threats of substitute products and rivalry among existing competitors.
  • SWOT Analysis: An insightful SWOT framework, highlighting the strengths, weaknesses, opportunities and threats in the domain. Additionally, it provides Harvey ball analysis, highlighting the relative impact of each SWOT parameter.
  • Value Chain Analysis: A comprehensive analysis of the value chain, providing information on the different phases and stakeholders involved in the AI in oncology market.

Key Questions Answered in this Report

  • What is the current and future market size?
  • Who are the leading companies in this market?
  • What are the growth drivers that are likely to influence the evolution of this market?
  • What are the key partnership and funding trends shaping this industry?
  • Which region is likely to grow at higher CAGR till 2040?
  • How is the current and future market opportunity likely to be distributed across key market segments?

Reasons to Buy this Report

  • Detailed Market Analysis: The report provides a comprehensive market analysis, offering detailed revenue projections of the overall market and its specific sub-segments. This information is valuable to both established market leaders and emerging entrants.
  • In-depth Analysis of Trends: Stakeholders can leverage the report to gain a deeper understanding of the competitive dynamics within the market. Each report maps ecosystem activity across partnerships, funding, and patent landscapes to reveal growth hotspots and white spaces in the industry.
  • Opinion of Industry Experts: The report features extensive interviews and surveys with key opinion leaders and industry experts to validate market trends mentioned in the report.
  • Decision-ready Deliverables: The report offers stakeholders with strategic frameworks (Porter's Five Forces, value chain, SWOT), and complimentary Excel / slide packs with customization support.

Additional Benefits

  • Complimentary Dynamic Excel Dashboards for Analytical Modules
  • Exclusive 15% Free Content Customization
  • Personalized Interactive Report Walkthrough with Our Expert Research Team
  • Free Report Updates for Versions Older than 6-12 Months

TABLE OF CONTENTS

1. PREFACE

  • 1.1. Overview
  • 1.2. Scope of the Report
  • 1.3. Market Segmentation
  • 1.4. Research Methodology
  • 1.5. Key Questions Answered
  • 1.6. Chapter Outlines

2. EXECUTIVE SUMMARY

  • 2.1 Chapter Overview

3. INTRODUCTION

  • 3.1. Chapter Overview
  • 3.2. Overview of Artificial Intelligence
  • 3.3. Types Of Artificial Intelligence
  • 3.4. Role of AI in Oncology
  • 3.5. Key Challenges Associated with Use of AI
  • 3.6. Future Perspectives

4. MARKET OVERVIEW

  • 4.1. Chapter Overview
  • 4.2. AI in Oncology: Market Landscape of Software providers
    • 4.2.1. Analysis by Year of Establishment
    • 4.2.2. Analysis by Company Size
    • 4.2.3. Analysis by Location of Headquarters (Region-wise)
    • 4.2.4. Analysis by Location of Headquarters (Country-wise)
    • 4.2.5. Analysis by Type of End-User
    • 4.2.6. Analysis by Year of Establishment, Company size and Location of Headquarters
  • 4.3. AI in Oncology: Market Landscape of Software Solutions
    • 4.3.1. Analysis by Type of Service(s) Offered
    • 4.3.2. Analysis by Type of AI Technology Used
    • 4.3.3. Analysis by Type of Platform
    • 4.3.4. Analysis by Type of Service(s) Offered and Type of End-User
    • 4.3.5. Analysis by Type of Platform and Type of AI Technology Used
    • 4.3.6. Analysis by Type of Service(s) Offered, Location of Headquarters and Type of AI Technology Used

5. COMPANY PROFILES

  • 5.1. Chapter Overview
  • 5.2. Roche Diagnostics
    • 5.2.1. Company Overview
    • 5.2.2. Financial Information
    • 5.2.3. Service Portfolio
    • 5.2.4. Recent Developments and Future Outlook
  • 5.3. IBM Watson Health
    • 5.3.1. Company Overview
    • 5.3.2. Financial Information
    • 5.3.3. Service Portfolio
    • 5.3.4. Recent Developments and Future Outlook
  • 5.4. CancerCenter.AI
    • 5.4.1. Company Overview
    • 5.4.2. Service Portfolio
    • 5.4.3. Recent Development and Future Outlooks
  • 5.5. GE Healthcare
    • 5.5.1. Company Overview
    • 5.5.2. Financial Information
    • 5.5.3. Service Portfolio
    • 5.5.4. Recent Development and Future Outlook
  • 5.6. Concert AI
    • 5.6.1. Company Overview
    • 5.6.2. Service Portfolio
    • 5.6.3. Recent Developments and Future Outlook
  • 5.7. Path AI
    • 5.7.1. Company Overview
    • 5.7.2. Service portfolio
    • 5.7.3. Recent Development and Future Outlook
  • 5.8. Berg
    • 5.8.1. Company Overview
    • 5.8.2. Service Portfolio
    • 5.8.3. Recent Development and Future Outlook
  • 5.9. Median Technologies
    • 5.9.1. Company Overview
    • 5.9.2. Financial Information
    • 5.9.3. Service Portfolio
    • 5.9.4. Recent Development and Future Outlook
  • 5.10. iCAD
    • 5.10.1. Company Overview
    • 5.10.2. Financial Information
    • 5.10.3. Service Portfolio
    • 5.10.4. Recent Developments and Future Outlook
  • 5.11. JLK Inspection
    • 5.11.1. Company Overview
    • 5.11.2. Service Portfolio
    • 5.11.3. Recent Development and Future Outlook

6. COMPANY COMPETITIVENESS ANALYSIS

  • 6.1. Chapter Overview
  • 6.2. Assumptions and Key Parameters
  • 6.3. Methodology
    • 6.3.1. Company Competitiveness: Small Companies in North America
    • 6.3.2. Company Competitiveness: Small Companies in Europe
    • 6.3.3. Company Competitiveness: Small Companies in Asia Pacific
    • 6.3.4. Company Competitiveness: Mid-sized companies in North America
    • 6.3.5. Company Competitiveness: Mid-sized companies in Europe
    • 6.3.6. Company Competitiveness: Mid-sized companies in Asia Pacific
    • 6.3.7. Company Competitiveness: Large companies in North America and Europe

7. PATENT ANALYSIS

  • 7.1. Chapter Overview
  • 7.2. Scope and Methodology
  • 7.3. AI in Oncology: Patent Analysis
    • 7.3.1. Analysis by Type of Patent
    • 7.3.2. Analysis by Patent Publication Year
    • 7.3.3. Analysis by Year-wise Trend of Filed Patent Applications and Granted Patents
    • 7.3.4. Analysis by Jurisdiction
    • 7.3.5. Analysis by Type of Industry
    • 7.3.6. Analysis by Patent Age
    • 7.3.7. Analysis by Legal Status
    • 7.3.8. Analysis by CPC Symbols
    • 7.3.9. Most Active Players: Analysis by Number of Patents
    • 7.3.10. Analysis by Key Inventors
  • 7.4. AI in Oncology: Patent Benchmarking Analysis
    • 7.4.1. Analysis by Patent Characteristics
    • 7.4.2. AI in Oncology: Patent Valuation Analysis

8. PARTNERSHIPS AND COLLABORATIONS

  • 8.1. Chapter Overview
  • 8.2. Partnership Models
  • 8.3 AI in Oncology: Recent Partnerships and Collaborations
    • 8.3.1. Analysis by Year of Partnership
    • 8.3.2. Analysis by Type of Partnership
    • 8.3.3. Analysis by Year and Type of Partnership
    • 8.3.4. Analysis by Company Size and Type of Partnership
    • 8.3.5. Most Active Partners: Analysis by Number of Partnerships
    • 8.3.6. Most Active Players: Analysis by Type of Partnership
    • 8.3.7. Analysis by Type of Cancer
    • 8.3.8. Analysis by Type of Partner
    • 8.3.9. Analysis by Year and Type of Partner
    • 8.3.10. Intercontinental and Intracontinental Agreements
    • 8.3.11. Local and International Agreements
    • 8.3.12. Country-Wise Distribution
    • 8.3.13. Analysis by Region

9. FUNDING AND INVESTMENT ANALYSIS

  • 9.1. Chapter Overview
  • 9.2. Types of Funding Models
  • 9.3. AI in Oncology: List of Funding and Investment Analysis
    • 9.3.1. Analysis by Year and Number of Funding Instances
    • 9.3.2. Analysis by Year and Amount Invested
    • 9.3.3 Analysis by Type of Funding and Number of Instances
    • 9.3.4. Analysis by Year, Type of Funding and Amount Invested
    • 9.3.5. Analysis by Type of Funding and Amount Invested
    • 9.3.6. Analysis by Area of Application
    • 9.3.7. Analysis by Focus Area
    • 9.3.8. Analysis by Type of Cancer Indication
    • 9.3.9. Analysis by Geography
    • 9.3.10. Most Active Players by Number of Instances
    • 9.3.11. Most Active Players by Amount Invested
    • 9.3.12. Analysis by Type of Investors
    • 9.3.13. Analysis by Lead Investors
  • 9.4. Summary of Investments
  • 9.5. Concluding Remarks

10. BLUE OCEAN STRATEGY: A STRATEGIC GUIDE FOR START-UPS TO ENTER INTO HIGHLY COMPETITIVE MARKET

  • 10.1. Chapter Overview
  • 10.2. Overview of Blue Ocean Strategy
    • 10.2.1 Red Ocean
    • 10.2.2 Blue Ocean
    • 10.2.3 Difference between Red Ocean Strategy and Blue Ocean Strategy
    • 10.2.4. AI in Oncology: Blue Ocean Strategy and Shift Tools
      • 10.2.4.1. Value Innovation
      • 10.2.4.2. Strategy Canvas
      • 10.2.4.3. Four Action Framework
      • 10.2.4.4. Eliminate-Raise-Reduce-Create (ERRC) Grid
      • 10.2.4.5. Six Path Framework
      • 10.2.4.6. Pioneer-Migrator-Settler (PMS) Map
      • 10.2.4.7. Three Tiers of Noncustomers
      • 10.2.4.8. Sequence of Blue Ocean Strategy
      • 10.2.4.9. Buyer Utility Map
      • 10.2.4.10. The Price Corridor of the Mass
      • 10.2.4.11. Four Hurdles to Strategy Execution
      • 10.2.4.12. Tipping Point Leadership
      • 10.2.4.13. Fair Process
  • 10.3. Conclusion

11. MARKET SIZING AND OPPORTUNITY ANALYSIS

  • 11.1. Chapter Overview
  • 11.2 Key Assumptions and Methodology
  • 11.3. Global Artificial Intelligence in Oncology Market
  • 11.4. Artificial Intelligence in Oncology Market: Analysis by Type of Cancer
    • 11.4.1. Artificial Intelligence in Oncology Market for Breast Cancer
    • 11.4.2. Artificial Intelligence in Oncology Market for Lung Cancer
    • 11.4.3. Artificial Intelligence in Oncology Market for Prostate Cancer
    • 11.4.4. Artificial Intelligence in Oncology Market for Colorectal Cancer
    • 11.4.5. Artificial Intelligence in Oncology Market for Brain Tumor
    • 11.4.6. Artificial Intelligence in Oncology Market for Solid Malignancies
    • 11.4.7. Artificial Intelligence in Oncology Market for Other Cancers
  • 11.5. Artificial Intelligence in Oncology Market: Analysis by Type of End-User
    • 11.5.1. Artificial Intelligence in Oncology Market for Hospitals
    • 11.5.2. Artificial Intelligence in Oncology Market for Pharmaceutical Companies
    • 11.5.3. Artificial Intelligence in Oncology Market for Research Institutes
    • 11.5.4. Artificial Intelligence in Oncology Market for Other End-Users
  • 11.6. Artificial Intelligence in Oncology Market: Analysis by Key Geographical Regions
    • 11.6.1. Artificial Intelligence in Oncology Market for North America
    • 11.6.2. Artificial Intelligence in Oncology Market for Europe
    • 11.6.3. Artificial Intelligence in Oncology Market for Asia Pacific
    • 11.6.4. Artificial Intelligence in Oncology Market for Rest of the World

12. CONCLUSION

  • 12.1. Chapter Overview

13. EXECUTIVE INSIGHTS

14. APPENDIX 1: TABULATED DATA

15. APPENDIX 2: LIST OF COMPANIES AND ORGANIZATIONS