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市场调查报告书

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1683384

日本医疗保健市场中的人工智慧 - 2025 至 2033 年

Japan AI in Healthcare Market - 2025-2033

出版日期: 2025年03月20日 | 出版商:

DataM Intelligence | 英文 176 Pages | 商品交期: 最快1-2个工作天内

价格

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简介目录

2024 年日本医疗保健人工智慧市场规模达到 14.2 亿美元，预计到 2033 年将达到 148 亿美元，2025-2033 年预测期内的复合年增长率为 36.5%。

日本医疗市场的人工智慧正在利用人工智慧（AI）技术来增强诊断、治疗计划、药物开发和患者管理系统，从而改变医疗保健产业。人工智慧分析X光、CT扫描和MRI扫描等医学影像，以提高诊断的准确性和速度。 LPixel 和富士胶片株式会社等公司在该领域处于领先地位，其人工智慧演算法能够检测到人眼无法发现的异常。

人工智慧透过识别医学影像中的模式帮助早期发现癌症，显着改善诊断结果。人工智慧可以透过分析患者资料和病史来预测疾病进展并协助预防医学。这种预测能力可以帮助医疗保健提供者采取主动措施来管理慢性病，并有助于根据基因特征和病史为个别患者量身定制治疗方案，从而提高治疗效果和患者治疗效果。

市场动态：

驱动因素与约束因素

技术进步

预计预测期内技术进步将推动日本医疗保健市场人工智慧的成长。日本的人工智慧医疗新创公司正在迅速发展，新工具旨在提高癌症、流感和心臟病等疾病的诊断速度和准确性。然而，整合这些人工智慧工具面临挑战，例如新产品的审批流程漫长。儘管存在这些障碍，但全球在管理道德风险和製定标准方面的努力有望帮助克服障碍，促进人工智慧在增强日本医疗保健体系方面发挥作用。

日本医疗保健领域的人工智慧整合正在改变诊断和治疗流程。重点领域包括用于提高癌症等疾病检测准确性的医学影像、用于个人化治疗和预测疾病进展的预测分析，以及用于协助手术和护理支援的医疗机器人。这些技术解决了日本人口老化和劳动力短缺等挑战。成长动力包括人工智慧的进步、政府支持和市场潜力，预测到 2027 年将大幅扩张。

此外，产业的主要参与者应推出创新产品，推动日本医疗保健市场人工智慧的发展。例如，2024 年 11 月，日本在医疗保健技术领域迅速发展，重点关注下一代药物设计、医疗机器人和数位健康平台。利用人工智慧，该国旨在应对人口老化和医疗人员短缺等各种挑战，同时提高医疗品质。

此外，2024 年 6 月，软银集团与 Tempus AI 成立了一家合资企业，名为 SB Tempus，旨在透过人工智慧精准医疗改变日本的医疗保健。该合作伙伴将利用人工智慧分析个人医疗资料（包括基因资讯），以提供个人化的治疗方案。该合资公司最初的重点是肿瘤学，将有助于制定针对性的治疗方法，改善医疗保健效果。

资料隐私问题

资料隐私和监管挑战是人工智慧技术融入日本医疗保健市场的主要障碍。随着人工智慧在诊断、预测分析和个人化医疗等领域变得越来越普遍，它为敏感健康资料（包括医疗记录、基因资料和患者病史）的安全和使用带来了新的风险。

日本的《个人资讯保护法》（APPI）等严格的隐私法对医疗保健提供者提出了严格的要求，以确保患者资料安全，并且仅在患者同意的情况下共享。然而，人工智慧系统通常需要大量资料才能有效运行，这引发了对资料外洩、身分盗窃和资讯滥用的担忧。因此，上述因素可能会限制日本医疗保健市场人工智慧的潜在成长。

市场领导者和先驱者
- 新兴先锋和杰出参与者
- 拥有最大销售品牌的既定领导者
- 拥有成熟产品的市场领导者
CXO 观点
最新进展与突破
案例研究/正在进行的研究
监管和报销情况
- 北美洲
- 欧洲
- 亚太地区
- 拉丁美洲
- 中东和非洲
波特五力分析
供应链分析
专利分析
SWOT 分析
未满足的需求和差距
市场进入和扩张的推荐策略
情境分析：最佳情况、基本情况和最坏情况预测
定价分析和价格动态
关键意见领袖

第 5 章：日本医疗保健市场中的人工智慧（按组成部分）

硬体
软体解决方案
服务

第 6 章：日本医疗保健市场中的人工智慧（按技术）

机器学习
自然语言处理
情境感知计算
电脑视觉

第 7 章：日本医疗保健市场中的人工智慧（按应用）

重症监护
机器人辅助手术
虚拟护理助理
行政工作流程助理
诈欺侦测
网路安全
减少剂量误差
医疗诊断
精准医疗
药物研发
远端病人监控
穿戴式装置
其他的

第 8 章：日本医疗保健市场中的人工智慧（按最终用户划分）

医疗保健提供者
医疗保健付款人
医疗保健公司
患者
其他的

第九章：竞争格局与市场定位

竞争概况和主要市场参与者
市占率分析与定位矩阵
策略伙伴关係、併购
产品组合和创新的关键发展
公司基准化分析

第十章：公司简介

公司概况
产品组合
- 产品描述
- 产品关键绩效指标 (KPI)
- 历史和预测产品销售量
- 产品销售量
财务概览
- 公司收入
- 地区收入份额
- 收入预测
主要进展
- 合併与收购
- 关键产品开发活动
- 监管部门批准等
SWOT 分析

FUJITSU
Microsoft
Cyberdyne Care Robotics GmbH
LPIXEL.
Rakuten Group, Inc.
MOLCURE Inc.
Medmain Inc.
AI Medical Service Inc.

第 11 章：假设与研究方法

资料收集方法
数据三角测量
预测技术
数据验证和确认

第 12 章：附录

简介目录

Product Code: HCIT9340

The Japan AI in healthcare market reached US$ 1.42 billion in 2024 and is expected to reach US$ 14.8 billion by 2033, growing at a CAGR of 36.5% during the forecast period 2025-2033.

Japan's AI in the healthcare market is transforming the healthcare sector by leveraging artificial intelligence (AI) technologies to enhance diagnostics, treatment planning, drug development, and patient management systems. AI analyzes medical images such as X-rays, CT scans, and MRI scans to improve diagnostic accuracy and speed. Companies like LPixel and Fujifilm Corporation are leading in this area, with AI algorithms capable of detecting abnormalities that may not be visible to the human eye.

AI helps in the early detection of cancers by identifying patterns in medical images, significantly improving diagnostic outcomes. AI can predict disease progression and aid in preventive medicine by analyzing patient data and medical histories. This predictive capability helps healthcare providers take proactive measures to manage chronic conditions and aids in tailoring treatments to individual patients based on genetic profiles and medical histories, enhancing treatment effectiveness and patient outcomes.

Market Dynamics: Drivers & Restraints

Technological Advancements

The technological advancements are expected to drive the growth of Japan's AI in the healthcare market in the forecast period. Japan's AI healthcare start-up scene is rapidly growing, with new tools aimed at improving diagnostic speed and accuracy for diseases like cancer, influenza, and heart disease. However, integrating these AI tools faces challenges, such as a lengthy approval process for new products. Despite these hurdles, global efforts to manage ethical risks and set standards are expected to help overcome barriers, facilitating AI's role in enhancing Japan's healthcare system.

AI integration in Japan's healthcare sector is transforming diagnostic and treatment processes. Key areas include medical imaging for improved accuracy in detecting diseases like cancer, predictive analytics to personalize treatments and predict disease progression, and healthcare robotics for assisting surgeries and nursing support. These technologies address challenges like Japan's aging population and labor shortages. Growth drivers include advancements in AI, government support, and the market's potential, with forecasts showing significant expansion by 2027. AI is revolutionizing healthcare by enhancing precision, efficiency, and patient care outcomes.

Additionally, key players in the industry should launch innovative launches that would drive Japan's AI in the healthcare market growth. For instance, in November 2024, Japan is rapidly advancing in healthcare technology, focusing on next-generation drug design, healthcare robotics, and digital health platforms. Leveraging AI, the country aims to tackle various challenges, such as its aging population and shortage of healthcare workers, while improving the quality of medical care.

Also, in June 2024, SoftBank Group launched a joint venture with Tempus AI, named SB Tempus, aimed at transforming healthcare in Japan through AI-powered precision medicine. The partnership will utilize AI to analyze personal medical data, including genetic information, to offer personalized treatment plans. With an initial focus on oncology, this venture will help tailor targeted therapies, improving healthcare outcomes.

Data Privacy Concerns

Data privacy and regulatory challenges are major barriers to the integration of AI technologies into Japan's healthcare market. As AI becomes increasingly prevalent in areas like diagnostics, predictive analytics, and personalized medicine, it creates new risks surrounding the security and use of sensitive health data, including medical records, genetic data, and patient histories.

Japan's strict privacy laws, such as the Act on the Protection of Personal Information (APPI), impose significant requirements on healthcare providers to ensure patient data is secure and only shared with patient consent. However, AI systems often require vast amounts of data to function effectively, which raises concerns about data breaches, identity theft, and misuse of information. Thus, the above factors could be limiting Japan's AI in the healthcare market's potential growth.

Segment Analysis

The Japan AI in the healthcare market is segmented based on component, technology, application, and end-user.

Component:

The software solutions segment in the component is expected to dominate the Japan AI in the healthcare market share

The software solutions segment in Japan's AI in Healthcare market revolves around the development and deployment of AI-powered software designed to improve the efficiency, accuracy, and overall effectiveness of various healthcare functions, including diagnostics, treatment planning, and patient management. These solutions are pivotal in enhancing patient outcomes and streamlining healthcare processes.

AI-driven algorithms are used to enhance the analysis of medical images such as X-rays, CT scans, and MRIs, aiding in quicker and more precise diagnoses. Companies like LPixel and Fujifilm Corporation are at the forefront of applying AI to detect abnormalities, such as tumors or cardiovascular conditions. AI tools analyze vast amounts of patient data to predict potential diseases or health risks. By leveraging patient history, genetic information, and other medical records, these systems enable personalized treatment plans and early interventions, ultimately improving patient care outcomes.

Additionally, key players in the industry have innovative launches that would drive this segment growth in the Japan AI in healthcare market. For instance, in November 2023, RapidAI, a health tech company, received Class III Shonin clearance in Japan, allowing it to launch its Rapid Edge Cloud platform and a non-contrast CT tool for stroke identification. RapidAI's offerings include diagnostic solutions for stroke, aneurysms, and pulmonary embolisms. It also provides technology platforms for coordinated care between hospitals and EMS providers, analytics software for hospital operations, and a clinical trial platform to streamline screening and enrollment. These factors have solidified the segment's position in the Japanese AI in healthcare market.

Competitive Landscape

The major players in the Japan AI in healthcare market include IBM, FUJITSU, Microsoft, Cyberdyne Care Robotics GmbH, LPIXEL., Rakuten Group, Inc., MOLCURE Inc., Medmain Inc., and AI Medical Service Inc., among others.

Key Developments

In November 2024, NVIDIA launched the BioNeMo framework to accelerate digital biology for the biopharma sector. This open-source platform is designed to help researchers in drug discovery and molecular design by scaling AI models for biomolecular research. The framework includes tools that enable the rapid development of large-scale models, such as AlphaFold2 for protein structure prediction and DiffDock 2.0 for faster and more accurate molecular docking predictions. The platform supports integration with existing high-performance computing systems, significantly enhancing research capabilities.

Why Purchase the Report?

Pipeline & Innovations: Reviews ongoing clinical trials and product pipelines and forecasts upcoming advancements in medical devices and pharmaceuticals.
Product Performance & Market Positioning: Analyze product performance, market positioning, and growth potential to optimize strategies.
Real-World Evidence: Integrates patient feedback and data into product development for improved outcomes.
Physician Preferences & Health System Impact: Examines healthcare provider behaviors and the impact of health system mergers on adoption strategies.
Market Updates & Industry Changes: This covers recent regulatory changes, new policies, and emerging technologies.
Competitive Strategies: Analyze competitor strategies, market share, and emerging players.
Pricing & Market Access: Reviews pricing models, reimbursement trends, and market access strategies.
Market Entry & Expansion: Identifies optimal strategies for entering new markets and partnerships.
Regional Growth & Investment: Highlights high-growth regions and investment opportunities.
Supply Chain Optimization: Assesses supply chain risks and distribution strategies for efficient product delivery.
Sustainability & Regulatory Impact: Focuses on eco-friendly practices and evolving regulations in healthcare.
Post-market Surveillance: Uses post-market data to enhance product safety and access.
Pharmacoeconomics & Value-Based Pricing: Analyzes the shift to value-based pricing and data-driven decision-making in R&D.

The Japan AI in Healthcare Market report delivers a detailed analysis with 60+ key tables, more than 50 visually impactful figures, and 176 pages of expert insights, providing a complete view of the market landscape.

Target Audience 2024

Manufacturers: Pharmaceutical, Medical Device, Biotech Companies, Contract Manufacturers, Distributors, Hospitals.
Regulatory & Policy: Compliance Officers, Government, Health Economists, Market Access Specialists.
Technology & Innovation: AI/Robotics Providers, R&D Professionals, Clinical Trial Managers, Pharmacovigilance Experts.
Investors: Healthcare Investors, Venture Fund Investors, Pharma Marketing & Sales.
Consulting & Advisory: Healthcare Consultants, Industry Associations, Analysts.
Supply Chain: Distribution and Supply Chain Managers.
Consumers & Advocacy: Patients, Advocacy Groups, Insurance Companies.
Academic & Research: Academic Institutions.

1. Market Introduction and Scope

1.1. Objectives of the Report
1.2. Report Coverage & Definitions
1.3. Report Scope

2. Executive Insights and Key Takeaways

2.1. Market Highlights and Strategic Takeaways
2.2. Key Trends and Future Projections
2.3. Snippet by Component
2.4. Snippet by Technology
2.5. Snippet by Application
2.6. Snippet by End-User

3. Dynamics

3.1. Impacting Factors
- 3.1.1. Drivers
  - 3.1.1.1. Technological Advancements
  - 3.1.1.2. Rising Aging Population and Healthcare Needs
- 3.1.2. Restraints
  - 3.1.2.1. Data Privacy Concerns
  - 3.1.2.2. Stringent Regulatory Environment
- 3.1.3. Opportunity
  - 3.1.3.1. Investment in Precision Medicine
- 3.1.4. Impact Analysis

4. Strategic Insights and Industry Outlook

4.1. Market Leaders and Pioneers
- 4.1.1. Emerging Pioneers and Prominent Players
- 4.1.2. Established leaders with largest-selling Brand
- 4.1.3. Market leaders with established Product
4.2. CXO Perspectives
4.3. Latest Developments and Breakthroughs
4.4. Case Studies/Ongoing Research
4.5. Regulatory and Reimbursement Landscape
- 4.5.1. North America
- 4.5.2. Europe
- 4.5.3. Asia Pacific
- 4.5.4. Latin America
- 4.5.5. Middle East & Africa
4.6. Porter's Five Forces Analysis
4.7. Supply Chain Analysis
4.8. Patent Analysis
4.9. SWOT Analysis
4.10. Unmet Needs and Gaps
4.11. Recommended Strategies for Market Entry and Expansion
4.12. Scenario Analysis: Best-Case, Base-Case, and Worst-Case Forecasts
4.13. Pricing Analysis and Price Dynamics
4.14. Key Opinion Leaders

5. Japan AI in Healthcare Market, By Component

5.1. Introduction
- 5.1.1. Analysis and Y-o-Y Growth Analysis (%), By Component
- 5.1.2. Market Attractiveness Index, By Component
5.2. Hardware*
- 5.2.1. Introduction
- 5.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
5.3. Software Solutions
5.4. Services

6. Japan AI in Healthcare Market, By Technology

6.1. Introduction
- 6.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Technology
- 6.1.2. Market Attractiveness Index, By Technology
6.2. Machine Learning*
- 6.2.1. Introduction
- 6.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
6.3. Natural Language Processing
6.4. Context-Aware Computing
6.5. Computer Vision

7. Japan AI in Healthcare Market, By Application

7.1. Introduction
- 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 7.1.2. Market Attractiveness Index, By Application
7.2. Critical Care*
- 7.2.1. Introduction
- 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
7.3. Robot-Assisted Surgery
7.4. Virtual Nursing Assistants
7.5. Administrative Workflow Assistants
7.6. Fraud Detection
7.7. Cybersecurity
7.8. Dosage Error Reduction
7.9. Medical Diagnostics
7.10. Precision Medicine
7.11. Drug Discovery & Development
7.12. Remote Patient Monitoring
7.13. Wearables
7.14. Others

8. Japan AI in Healthcare Market, By End-User

8.1. Introduction
- 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 8.1.2. Market Attractiveness Index, By End-User
8.2. Healthcare Providers*
- 8.2.1. Introduction
- 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
8.3. Healthcare Payers
8.4. Healthcare Companies
8.5. Patients
8.6. Others

9. Competitive Landscape and Market Positioning

9.1. Competitive Overview and Key Market Players
9.2. Market Share Analysis and Positioning Matrix
9.3. Strategic Partnerships, Mergers & Acquisitions
9.4. Key Developments in Product Portfolios and Innovations
9.5. Company Benchmarking

10. Company Profiles

10.1. IBM *
- 10.1.1. Company Overview
- 10.1.2. Product Portfolio
  - 10.1.2.1. Product Description
  - 10.1.2.2. Product Key Performance Indicators (KPIs)
  - 10.1.2.3. Historic and Forecasted Product Sales
  - 10.1.2.4. Product Sales Volume
- 10.1.3. Financial Overview
  - 10.1.3.1. Company Revenue's
  - 10.1.3.2. Geographical Revenue Shares
  - 10.1.3.3. Revenue Forecasts
- 10.1.4. Key Developments
  - 10.1.4.1. Mergers & Acquisitions
  - 10.1.4.2. Key Product Development Activities
  - 10.1.4.3. Regulatory Approvals, etc.
- 10.1.5. SWOT Analysis
10.2. FUJITSU
10.3. Microsoft
10.4. Cyberdyne Care Robotics GmbH
10.5. LPIXEL.
10.6. Rakuten Group, Inc.
10.7. MOLCURE Inc.
10.8. Medmain Inc.
10.9. AI Medical Service Inc.