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市場調查報告書

商品編碼

1683384

日本醫療保健市場中的人工智慧 - 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個工作天內

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簡介目錄

2024 年日本醫療保健人工智慧市場規模達到 14.2 億美元，預計到 2033 年將達到 148 億美元，2025-2033 年預測期內的複合年成長率為 36.5%。

日本醫療市場的人工智慧正在利用人工智慧（AI）技術來增強診斷、治療計劃、藥物開發和患者管理系統，從而改變醫療保健產業。人工智慧分析X光、CT掃描和MRI掃描等醫學影像，以提高診斷的準確性和速度。 LPixel 和富士膠片株式會社等公司在該領域處於領先地位，其人工智慧演算法能夠檢測到人眼無法發現的異常。

人工智慧透過識別醫學影像中的模式幫助早期發現癌症，顯著改善診斷結果。人工智慧可以透過分析患者資料和病史來預測疾病進展並協助預防醫學。這種預測能力可以幫助醫療保健提供者採取主動措施來管理慢性病，並有助於根據基因特徵和病史為個別患者量身定做治療方案，從而提高治療效果和患者治療效果。

市場動態：

促進因素與約束因素

技術進步

預計預測期內技術進步將推動日本醫療保健市場人工智慧的成長。日本的人工智慧醫療新創公司正在迅速發展，新工具旨在提高癌症、流感和心臟病等疾病的診斷速度和準確性。然而，整合這些人工智慧工具面臨挑戰，例如新產品的核准流程漫長。儘管存在這些障礙，但全球在管理道德風險和製定標準方面的努力有望幫助克服障礙，促進人工智慧在增強日本醫療保健體系方面發揮作用。

日本醫療保健領域的人工智慧整合正在改變診斷和治療流程。重點領域包括用於提高癌症等疾病檢測準確性的醫學影像、用於個人化治療和預測疾病進展的預測分析，以及用於協助手術和護理支援的醫療機器人。這些技術解決了日本人口老化和勞動力短缺等挑戰。成長動力包括人工智慧的進步、政府支持和市場潛力，預測到 2027 年將大幅擴張。

此外，產業的主要參與者應推出創新產品，推動日本醫療保健市場人工智慧的發展。例如，2024 年 11 月，日本在醫療保健技術領域迅速發展，重點關注下一代藥物設計、醫療機器人和數位健康平台。利用人工智慧，該國旨在應對人口老化和醫療人員短缺等各種挑戰，同時提高醫療品質。

此外，2024 年 6 月，軟銀集團與 Tempus AI 成立了一家合資企業，名為 SB Tempus，旨在透過人工智慧精準醫療改變日本的醫療保健。該合作夥伴將利用人工智慧分析個人醫療資料（包括基因資訊），以提供個人化的治療方案。該合資公司最初的重點是腫瘤學，將有助於制定針對性的治療方法，改善醫療保健效果。

資料隱私問題

資料隱私和監管挑戰是人工智慧技術融入日本醫療保健市場的主要障礙。隨著人工智慧在診斷、預測分析和個人化醫療等領域變得越來越普遍，它為敏感健康資料（包括醫療記錄、基因資料和患者病史）的安全和使用帶來了新的風險。

日本的《個人資訊保護法》（APPI）等嚴格的隱私法對醫療保健提供者提出了嚴格的要求，以確保患者資料安全，並且僅在患者同意的情況下共享。然而，人工智慧系統通常需要大量資料才能有效運行，這引發了對資料外洩、身分盜竊和資訊濫用的擔憂。因此，上述因素可能會限制日本醫療保健市場人工智慧的潛在成長。

市場領導者和先驅者
- 新興先鋒和傑出參與者
- 擁有最大銷售品牌的既定領導者
- 擁有成熟產品的市場領導者
CXO 觀點
最新進展與突破
案例研究/正在進行的研究
監管和報銷情況
- 北美洲
- 歐洲
- 亞太地區
- 拉丁美洲
- 中東和非洲
波特五力分析
供應鏈分析
專利分析
SWOT 分析
未滿足的需求和差距
市場進入和擴張的推薦策略
情境分析：最佳情況、基本情況和最壞情況預測
定價分析和價格動態
關鍵意見領袖

第 5 章：日本醫療保健市場中的人工智慧（按組成部分）

硬體
軟體解決方案
服務

第 6 章：日本醫療保健市場中的人工智慧（按技術）

機器學習
自然語言處理
情境感知計算
電腦視覺

第 7 章：日本醫療保健市場中的人工智慧（按應用）

重症監護
機器人輔助手術
虛擬護理助理
行政工作流程助理
詐欺偵測
網路安全
減少劑量誤差
醫療診斷
精準醫療
藥物研發
遠端病人監控
穿戴式裝置
其他

第 8 章：日本醫療保健市場中的人工智慧（按最終用戶分類）

醫療保健提供者
醫療保健付款人
醫療保健公司
患者
其他

第9章：競爭格局與市場定位

競爭概況和主要市場參與者
市佔率分析與定位矩陣
策略夥伴關係、併購
產品組合和創新的關鍵發展
公司基準化分析

第10章：公司簡介

公司概況
產品組合
- 產品描述
- 產品關鍵績效指標 (KPI)
- 歷史和預測產品銷售量
- 產品銷售量
財務概覽
- 公司收入
- 地區收入佔有率
- 收入預測
主要進展
- 合併與收購
- 關鍵產品開發活動
- 監管部門批准等
SWOT 分析

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

第 11 章：假設與研究方法

資料收集方法
數據三角測量
預測技術
數據驗證和確認

第 12 章：附錄

簡介目錄

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.