의료 분야 디지털 트윈 시장(-2031년) : 컴포넌트(소프트웨어 및 서비스), 용도(맞춤형 의료, Drug Discovery, 의료 교육, 워크플로우 최적화), 최종사용자(의료 제공업체, 연구 및 학술기관, 보험자), 지역별

The global digital twin healthcare market is experiencing significant growth in 2025, driven by the increasing adoption of digital twins in healthcare and rising investments by public & private entities. The market is projected to reach USD 101.19 billion by 2031 from USD 7.47 billion in 2026, at a CAGR of 68.4% during the forecast period. There have been many investments in digital twins by both public and private organizations due to their innovation potential.

For instance, Quibim, based in Valencia, is developing the use of imaging biomarkers in precision medicine. Quibim has made an announcement on its successful raising of funds amounting to USD 50.6 million as part of its series A investment round to establish a footprint in the USA market. According to Quibim, this will be a milestone in developing human digital twins. These are dynamic models that will make it possible to monitor the well-being of people while ensuring that drugs are developed efficiently.

"Surgical planning & medical education segment accounted for the second-largest share of the market during the forecast period, by application."

In 2025, the surgical planning & medical education segment accounted for the second-largest share of the digital twin in the healthcare market. The growth in this market was driven by the ability of digital twins to work with virtual reality applications that enable the residents to train by simulating surgical processes for the specific anatomical and physiological profile of the patients. This helps in generating a real-life performance depiction and facilitates the evaluation of the intraoperative metrics. Many companies have simulated human anatomy and surgery processes in order to reduce reliance on cadavers.

"By component, software accounted for the fastest growth during the forecast period."

Based on component, software is projected to witness the fastest growth in the digital twins in healthcare market during the forecast period. The reason behind such growth is associated with the rising number of adoptions of digital twin platforms in order to offer real-time simulation and predictive analytics. In particular, healthcare organizations and research institutions will start relying on software digital twin solutions to develop virtual models of patients, organs, and healthcare facilities based on information collected via imaging techniques, electronic health records, and wearable connected devices. Software digital twin solutions enable not only continuous monitoring but also predicting disease progression and creating personalized treatment plans. Rising interest in digital twin technology and software solutions is also explained by the growing adoption of platforms based on AI and cloud computing. In addition, the rising trend towards value-based care and precision medicine is anticipated to boost demand for digital twin software solutions. Furthermore, the ongoing investments in digital health solutions and the necessity of building interoperable systems capable of interacting with the IT infrastructures of hospitals contribute to such growth.

"Asia Pacific to witness the highest growth rate during the forecast period."

The market for digital twins in healthcare in the Asia Pacific region is growing at a fast pace, owing to increased clinical research activities and the adoption of digital technologies by healthcare providers. Asia Pacific has emerged as one of the major hubs for research activities, where countries like India, Japan, South Korea, and Australia have become prominent owing to improved regulation and lower cost structure. Pharmaceutical and biotechnology companies are increasingly engaging in research initiatives through the use of data and simulations, which is further driving the adoption of digital twin technologies. At the same time, significant investment is being made towards the development of digital health infrastructure in the form of artificial intelligence, cloud computing, and health IT systems, which are vital for the implementation of digital twin technologies. Furthermore, governments in the Asia Pacific region are working towards the digitalization of the healthcare industry to improve efficiency and performance. There have been recent developments in this regard. For example, the Japanese company Fujitsu Limited has developed digital twin technology in the healthcare sector using artificial intelligence-based simulation platforms for personalized medicine and decision-making in clinical processes.

The breakdown of primary participants is as follows:

• By Company Type - Tier 1: 45%, Tier 2: 30%, and Tier 3: 25%
• By Designation - C-level: 42%, Director-level: 31%, and Others: 27%
• By Region - North America: 45%, Europe: 30%, Asia Pacific: 20%, Latin America: 3%, and Middle East & Africa: 2%.

The key players operating in the digital twin in healthcare market include Microsoft Corporation (US), Siemens Healthineers AG (Germany), Koninklijke Philips N.V. (Netherlands), Amazon Web Services, Inc. (US), Dassault Systemes (France), GE Healthcare (US), IBM (US), NVIDIA Corporation (US), Oracle Corporation (US), PTC (US), SAP (Germany), Atos SE (France), ANSYS, Inc. (US), Faststream Technologies (US), Rescale, Inc. (US), Twin Health (US), NUREA (France), Predictiv (US), Verto (Canada), Qbio (US), Virtonomy GmbH (Germany), Unlearn.ai, Inc. (US), ThoughtWire (Canada), Sim and Cure (France), and PrediSurge (France).

• The study includes an in-depth competitive analysis of these key players in the digital twin in healthcare market, with their company profiles, recent developments, and key market strategies.

Research Coverage

The report analyzes the digital twins in healthcare market and aims to estimate the market size and future growth potential of various market segments, based on components, application, end user, and region. The report also provides a competitive analysis of the key players operating in this market, along with their company profiles, product offerings, recent developments, and key market strategies.

Reasons to buy this report

This report will enrich established firms as well as new entrants/smaller firms to gauge the pulse of the market, which, in turn, would help them garner a greater share of the market. Firms purchasing the report could use one or a combination of the following strategies to strengthen their positions in the market.

This report provides insights into:

• Analysis of key drivers (increasing Investments in digital twins in developed as well as emerging technology adoption, rising demand for personalized medicine, increasing funding and investments in digital twin startups), restraints (accuracy and privacy issues with digital twin systems and high implementation costs), opportunities (growing importance of digital twin Iin emerging market, increasing focus on cutting edge real-time data analytics), and challenges (lack of technical expertise & data management issues) influencing the growth of the digital twin market
• Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and product & service launches in the digital twins in healthcare market
• Market Development: Comprehensive information on the lucrative emerging markets, components, applications, end users, and regions
• Market Diversification: Exhaustive information about the product portfolios, growing geographies, recent developments, and investments in the digital twins in healthcare market
• Competitive Assessment: In-depth assessment of market shares, growth strategies, product offerings, and capabilities of the leading players in the digital twins in healthcare market like Microsoft Corporation (US), Siemens Healthineers AG (Germany), Koninklijke Philips N.V. (Netherlands), Amazon Web Services, Inc. (US), Dassault Systemes (France), GE Healthcare (US), IBM (US), NVIDIA Corporation (US), Oracle Corporation (US), PTC (US), SAP (Germany), Atos SE (France), ANSYS, Inc. (US), Faststream Technologies (US), Rescale, Inc. (US), Twin Health (US), NUREA (France), Predictiv (US), Verto (Canada), Qbio (US), Virtonomy GmbH (Germany), Unlearn.ai, Inc. (US), ThoughtWire (Canada), Sim and Cure (France), and PrediSurge (France)

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 STUDY OBJECTIVES
• 1.2 MARKET DEFINITION
• 1.3 STUDY SCOPE
  • 1.3.1 MARKET SEGMENTATION & REGIONAL SCOPE
  • 1.3.2 INCLUSIONS & EXCLUSIONS
  • 1.3.3 YEARS CONSIDERED
  • 1.3.4 CURRENCY CONSIDERED
• 1.4 STAKEHOLDERS
• 1.5 SUMMARY OF CHANGES

2 EXECUTIVE SUMMARY

• 2.1 KEY INSIGHTS AND MARKET HIGHLIGHTS
• 2.2 KEY MARKET PARTICIPANTS: SHARE INSIGHTS AND STRATEGIC DEVELOPMENTS
• 2.3 DISRUPTIVE TRENDS SHAPING THE MARKET
• 2.4 HIGH-GROWTH SEGMENTS & EMERGING FRONTIERS
• 2.5 SNAPSHOT: GLOBAL MARKET SIZE, GROWTH RATE, AND FORECAST

3 PREMIUM INSIGHTS

• 3.1 DIGITAL TWINS IN HEALTHCARE MARKET OVERVIEW
• 3.2 DIGITAL TWINS IN HEALTHCARE MARKET, BY COMPONENT & REGION
• 3.3 DIGITAL TWINS IN HEALTHCARE MARKET: REGIONAL SNAPSHOT

4 MARKET OVERVIEW

• 4.1 INTRODUCTION
• 4.2 MARKET DYNAMICS
  • 4.2.1 DRIVERS
    • 4.2.1.1 Increasing investments by public and private entities
    • 4.2.1.2 Growing applications of digital twins
    • 4.2.1.3 Technological advancements
    • 4.2.1.4 Growing funding and investments in digital twin startups
  • 4.2.2 RESTRAINTS
    • 4.2.2.1 Managing data quality, privacy issues, and high implementation costs
  • 4.2.3 OPPORTUNITIES
    • 4.2.3.1 Increasing focus on cutting-edge real-time data analytics
    • 4.2.3.2 Growing importance of digital twins in emerging economies
  • 4.2.4 CHALLENGES
    • 4.2.4.1 Lack of skilled professionals
    • 4.2.4.2 Integration with existing systems and outdated digital infrastructure
• 4.3 UNMET NEEDS AND WHITE SPACES
• 4.4 INTERCONNECTED MARKETS AND CROSS-SECTOR OPPORTUNITIES
• 4.5 STRATEGIC MOVES BY TIER-1/2/3 PLAYERS

5 INDUSTRY TRENDS

• 5.1 PORTER'S FIVE FORCES ANALYSIS
  • 5.1.1 INTENSITY OF COMPETITIVE RIVALRY (HIGH)
  • 5.1.2 BARGAINING POWER OF SUPPLIERS (LOW)
  • 5.1.3 BARGAINING POWER OF BUYERS (HIGH)
  • 5.1.4 THREAT OF NEW ENTRANTS (LOW)
  • 5.1.5 THREAT OF SUBSTITUTES (LOW)
• 5.2 MACROECONOMIC INDICATORS
  • 5.2.1 INTRODUCTION
  • 5.2.2 GDP TRENDS AND FORECAST
  • 5.2.3 TRENDS IN GLOBAL HEALTHCARE IT INDUSTRY
• 5.3 VALUE CHAIN ANALYSIS
  • 5.3.1 RESEARCH & PRODUCT DEVELOPMENT
  • 5.3.2 TECHNOLOGY INPUTS AND INFRASTRUCTURE
  • 5.3.3 PLATFORM DEVELOPMENT AND INTEGRATION
  • 5.3.4 DISTRIBUTION
  • 5.3.5 MARKETING AND SALES
  • 5.3.6 POST-SALE SERVICES
• 5.4 ECOSYSTEM ANALYSIS
• 5.5 PRICING ANALYSIS
  • 5.5.1 INDICATIVE PRICE FOR DIGITAL TWIN IN HEALTHCARE MARKET, BY TYPE (2025)
  • 5.5.2 INDICATIVE PRICE FOR DIGITAL TWIN IN HEALTHCARE MARKET, BY REGION (2025)
• 5.6 KEY CONFERENCES AND EVENTS, 2026-2027
• 5.7 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
• 5.8 INVESTMENT AND FUNDING SCENARIO
• 5.9 CASE STUDY ANALYSIS
• 5.10 IMPACT OF 2025 US TARIFF - DIGITAL TWIN IN HEALTHCARE MARKET
  • 5.10.1 INTRODUCTION
  • 5.10.2 KEY TARIFF RATES
  • 5.10.3 PRICE IMPACT ANALYSIS
  • 5.10.4 IMPACT ON COUNTRY/REGION
    • 5.10.4.1 US
    • 5.10.4.2 Europe
    • 5.10.4.3 Asia Pacific
  • 5.10.5 IMPACT ON END USERS
    • 5.10.5.1 Pharma & biopharma companies
    • 5.10.5.2 Research & academia
    • 5.10.5.3 Healthcare providers
    • 5.10.5.4 Medical device companies
    • 5.10.5.5 Other end users

6 STRATEGIC DISRUPTION THROUGH TECHNOLOGY, PATENTS, DIGITAL, AND AI ADOPTION

• 6.1 KEY EMERGING TECHNOLOGIES
  • 6.1.1 AI/ML AND SIMULATION MODELS
  • 6.1.2 CLOUD COMPUTING AND HIGH-PERFORMANCE COMPUTING
  • 6.1.3 DATA INTEGRATION PLATFORMS
• 6.2 COMPLEMENTARY TECHNOLOGIES
  • 6.2.1 INTERNET OF MEDICAL THINGS (IOMT) AND CONNECTED DEVICES
  • 6.2.2 MEDICAL IMAGING AND IMAGING AI
• 6.3 ADJACENT TECHNOLOGIES
  • 6.3.1 CLINICAL DECISION SUPPORT SYSTEMS
  • 6.3.2 AR/VR FOR SURGICAL SIMULATION AND TRAINING
• 6.4 TECHNOLOGY/PRODUCT ROADMAP
• 6.5 PATENT ANALYSIS
  • 6.5.1 PATENT PUBLICATION TRENDS FOR DIGITAL TWIN IN HEALTHCARE MARKET
  • 6.5.2 INSIGHTS: JURISDICTION AND TOP APPLICANT ANALYSIS
• 6.6 FUTURE APPLICATIONS
  • 6.6.1 AI-DRIVEN PREDICTIVE MODELING AND CLINICAL DECISION SUPPORT
  • 6.6.2 VIRTUAL THERAPEUTIC SIMULATION AND PERSONALIZED INTERVENTIONS
  • 6.6.3 VIRTUAL CLINICAL TRIALS AND HEALTH SYSTEM OPTIMIZATION
  • 6.6.4 POPULATION HEALTH MANAGEMENT AND PANDEMIC RESPONSE MODELING
• 6.7 IMPACT OF AI/GEN AI ON DIGITAL TWIN IN HEALTHCARE MARKET
  • 6.7.1 INTRODUCTION
  • 6.7.2 MARKET POTENTIAL OF AI/GEN AI IN DIGITAL TWIN IN HEALTHCARE MARKET
  • 6.7.3 CASE STUDIES RELATED TO AI/GEN AI IMPLEMENTATION
    • 6.7.3.1 AI-driven cardiac digital twin for personalized treatment planning
  • 6.7.4 IMPACT OF AI/GEN AI ON INTERCONNECTED AND ADJACENT ECOSYSTEMS
    • 6.7.4.1 Digital twin analytics & AI-driven simulation platforms
    • 6.7.4.2 Digital twin platform integration & regulatory infrastructure
    • 6.7.4.3 Clinical care, virtual monitoring & personalized therapeutics
  • 6.7.5 USER READINESS AND IMPACT ASSESSMENT
    • 6.7.5.1 User readiness
      • 6.7.5.1.1 User A: Pharma & biopharma companies
      • 6.7.5.1.2 User B: Research & academia
    • 6.7.5.2 Impact assessment
      • 6.7.5.2.1 User A: Pharma & biopharma companies
      • 6.7.5.2.2 User B: Research & academia

7 REGULATORY LANDSCAPE

• 7.1 REGIONAL REGULATIONS AND COMPLIANCE
  • 7.1.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • 7.1.2 REGULATORY FRAMEWORK
    • 7.1.2.1 North America
    • 7.1.2.2 Europe
    • 7.1.2.3 Asia Pacific
    • 7.1.2.4 Latin America
    • 7.1.2.5 Middle East & Africa
  • 7.1.3 INDUSTRY STANDARDS

8 CUSTOMER LANDSCAPE & BUYER BEHAVIOR

• 8.1 INTRODUCTION
• 8.2 DECISION-MAKING PROCESS
• 8.3 BUYER STAKEHOLDERS AND BUYING EVALUATION CRITERIA
  • 8.3.1 KEY STAKEHOLDERS IN BUYING PROCESS
  • 8.3.2 BUYING CRITERIA
• 8.4 ADOPTION BARRIERS & INTERNAL CHALLENGES
• 8.5 UNMET NEEDS FROM VARIOUS END-USE INDUSTRIES
  • 8.5.1 UNMET NEEDS
  • 8.5.2 END USER EXPECTATIONS
• 8.6 MARKET PROFITABILITY

9 DIGITAL TWINS IN HEALTHCARE MARKET, BY COMPONENT

• 9.1 INTRODUCTION
• 9.2 SERVICES
  • 9.2.1 INTRODUCTION OF COMPLEX SOFTWARE TO DRIVE DEMAND FOR SERVICES
• 9.3 SOFTWARE
  • 9.3.1 SHIFT TO WEB/CLOUD-BASED MODELS TO SUPPORT GROWTH

10 DIGITAL TWINS IN HEALTHCARE MARKET, BY TYPE

• 10.1 INTRODUCTION
• 10.2 PROCESS TWINS
  • 10.2.1 RISING DEMAND FOR HEALTHCARE WORKFLOWS AND OPERATIONAL PROCESSES TO BOOST ADOPTION
• 10.3 SYSTEM TWINS
  • 10.3.1 INCREASED DEMAND FOR OPERATIONAL EFFICIENCY IN HOSPITALS TO BOOST SEGMENT
• 10.4 WHOLE BODY TWINS
  • 10.4.1 ADVANCEMENTS IN AI AND ML TECHNOLOGIES TO BOOST MARKET
• 10.5 BODY PART TWINS
  • 10.5.1 RISING DEMAND FOR PERSONALIZED & PRECISION MEDICINE TO FUEL MARKET GROWTH

11 DIGITAL TWINS IN HEALTHCARE MARKET, BY APPLICATION

• 11.1 INTRODUCTION
• 11.2 DRUG DISCOVERY & DEVELOPMENT
  • 11.2.1 ABILITY OF DIGITAL TWINS TO ENHANCE DRUG DISCOVERY & DEVELOPMENT TO BOOST MARKET
• 11.3 PERSONALIZED MEDICINE
  • 11.3.1 QUICK AND COST-EFFECTIVE DEVELOPMENT AND TESTING OF PERSONALIZED DIAGNOSTICS TO SUPPORT MARKET
• 11.4 SURGICAL PLANNING & MEDICAL EDUCATION
  • 11.4.1 ABILITY TO ENHANCE SURGICAL TRAINING AND SIMULATE SURGICAL PROCEDURES TO BOOST ADOPTION
• 11.5 MEDICAL DEVICE DESIGN & TESTING
  • 11.5.1 POTENTIAL OF DIGITAL TWINS TO STREAMLINE OPERATIONS, MINIMIZE RISK, AND REDUCE DOWNTIME TO PROMOTE USE
• 11.6 HEALTHCARE WORKFLOW OPTIMIZATION & ASSET MANAGEMENT
  • 11.6.1 IMPROVED EFFICIENCY AND VALUABLE INSIGHTS TO SUPPORT DEMAND
• 11.7 OTHER APPLICATIONS

12 DIGITAL TWINS IN HEALTHCARE MARKET, BY END USER

• 12.1 INTRODUCTION
• 12.2 PHARMA & BIOPHARMA COMPANIES
  • 12.2.1 RISING DEMAND TO REDUCE TIME AND COST OF DRUG DEVELOPMENT TO BOOST ADOPTION
• 12.3 RESEARCH & ACADEMIA
  • 12.3.1 INTERACTIVE AND IMMERSIVE LEARNING EXPERIENCES OFFERED BY DIGITAL TWINS TO BOOST ADOPTION
• 12.4 HEALTHCARE PROVIDERS
  • 12.4.1 LOWER COSTS AND BETTER PATIENT TREATMENT TO FAVOR MARKET GROWTH
• 12.5 MEDICAL DEVICE COMPANIES
  • 12.5.1 GROWING USE OF DIGITAL TWINS FOR SOFTWARE OPTIMIZATION OF MEDICAL DEVICES TO FUEL GROWTH
• 12.6 OTHER END USERS

13 DIGITAL TWINS IN HEALTHCARE MARKET, BY REGION

• 13.1 INTRODUCTION
• 13.2 NORTH AMERICA
  • 13.2.1 MACROECONOMIC OUTLOOK FOR NORTH AMERICA
  • 13.2.2 US
    • 13.2.2.1 Expanding applications of digital twins in healthcare to bolster market growth
  • 13.2.3 CANADA
    • 13.2.3.1 National digital health strategy and AI-driven clinical research accelerating adoption
• 13.3 EUROPE
  • 13.3.1 MACROECONOMIC OUTLOOK FOR EUROPE
  • 13.3.2 GERMANY
    • 13.3.2.1 Hospital digitalization mandates and engineering-healthcare convergence drive market
  • 13.3.3 UK
    • 13.3.3.1 NHS digital transformation and in silico trial leadership advances digital twin market
  • 13.3.4 FRANCE
    • 13.3.4.1 National AI health strategy and clinical research infrastructure support digital twin integration
  • 13.3.5 ITALY
    • 13.3.5.1 National recovery plan investments and clinical research modernization drive adoption
  • 13.3.6 SPAIN
    • 13.3.6.1 Health system digital transformation and biomedical research network enables digital twin growth
  • 13.3.7 REST OF EUROPE
• 13.4 ASIA PACIFIC
  • 13.4.1 MACROECONOMIC OUTLOOK FOR ASIA PACIFIC
  • 13.4.2 JAPAN
    • 13.4.2.1 National Digital Health Mission and pharma innovation ecosystem emerging as digital twin growth frontier
  • 13.4.3 CHINA
    • 13.4.3.1 National AI strategy and smart hospital infrastructure to drive large-scale digital twin deployment
  • 13.4.4 INDIA
    • 13.4.4.1 Improvement in healthcare infrastructure to support market growth
  • 13.4.5 AUSTRALIA
    • 13.4.5.1 National Digital Health Strategy 2023-2028 and Medical Research Future Fund advance digital twin adoption
  • 13.4.6 SOUTH KOREA
    • 13.4.6.1 Smart Hospital Policy and deep tech industrial ecosystem position country as regional leader
  • 13.4.7 REST OF ASIA PACIFIC
• 13.5 LATIN AMERICA
  • 13.5.1 MACROECONOMIC OUTLOOK FOR LATIN AMERICA
  • 13.5.2 BRAZIL
    • 13.5.2.1 Country to dominate regional market
  • 13.5.3 MEXICO
    • 13.5.3.1 Favorable government strategies to drive market growth
  • 13.5.4 REST OF LATIN AMERICA
• 13.6 MIDDLE EAST & AFRICA
  • 13.6.1 MACROECONOMIC OUTLOOK FOR MIDDLE EAST & AFRICA
  • 13.6.2 GCC COUNTRIES
    • 13.6.2.1 Increasing healthcare infrastructure development and investment to support market growth
    • 13.6.2.2 Saudi Arabia
      • 13.6.2.2.1 Government-led digital transformation and strong investments in AI-driven healthcare
    • 13.6.2.3 UAE
      • 13.6.2.3.1 Advancing digital health innovation and strategic collaborations to drive digital biomarkers adoption
    • 13.6.2.4 Other GCC countries
      • 13.6.2.4.1 Regulatory initiatives, national health visions, and digital health infrastructure driving digital biomarkers adoption
  • 13.6.3 SOUTH AFRICA
    • 13.6.3.1 Rising healthcare demand and need for cost-efficient, data-driven care delivery drive adoption
  • 13.6.4 REST OF MIDDLE EAST & AFRICA

14 COMPETITIVE LANDSCAPE

• 14.1 OVERVIEW
• 14.2 KEY PLAYER STRATEGIES/RIGHT TO WIN
  • 14.2.1 OVERVIEW OF STRATEGIES ADOPTED BY KEY PLAYERS IN DIGITAL TWINS IN HEALTHCARE MARKET
• 14.3 REVENUE SHARE ANALYSIS OF TOP MARKET PLAYERS
• 14.4 MARKET SHARE ANALYSIS, 2025
• 14.5 BRAND/PRODUCT COMPARISON
• 14.6 VALUATION & FINANCIAL METRICS
  • 14.6.1 FINANCIAL METRICS
  • 14.6.2 COMPANY VALUATION
• 14.7 COMPANY EVALUATION QUADRANT: KEY PLAYERS, 2025
  • 14.7.1 STARS
  • 14.7.2 EMERGING LEADERS
  • 14.7.3 PERVASIVE PLAYERS
  • 14.7.4 PARTICIPANTS
  • 14.7.5 COMPANY FOOTPRINT: KEY PLAYERS, 2025
    • 14.7.5.1 Company footprint
    • 14.7.5.2 Region footprint
    • 14.7.5.3 Component footprint
    • 14.7.5.4 Type footprint
    • 14.7.5.5 Application footprint
    • 14.7.5.6 End user footprint
• 14.8 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2025
  • 14.8.1 PROGRESSIVE COMPANIES
  • 14.8.2 RESPONSIVE COMPANIES
  • 14.8.3 DYNAMIC COMPANIES
  • 14.8.4 STARTING BLOCKS
  • 14.8.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2025
    • 14.8.5.1 Detailed list of key startups/SME players
    • 14.8.5.2 Competitive benchmarking of key startups/SMEs
• 14.9 COMPETITIVE SCENARIO
  • 14.9.1 PRODUCT/SERVICE LAUNCHES, ENHANCEMENTS, AND APPROVALS
  • 14.9.2 DEALS
  • 14.9.3 OTHER DEVELOPMENTS

15 COMPANY PROFILES

• 15.1 KEY PLAYERS
  • 15.1.1 MICROSOFT
    • 15.1.1.1 Business overview
    • 15.1.1.2 Products/Services offered
    • 15.1.1.3 Recent developments
      • 15.1.1.3.1 Deals
    • 15.1.1.4 MnM view
      • 15.1.1.4.1 Key strengths
      • 15.1.1.4.2 Strategic choices
      • 15.1.1.4.3 Weaknesses & competitive threats
  • 15.1.2 SIEMENS HEALTHINEERS AG
    • 15.1.2.1 Business overview
    • 15.1.2.2 Products/Services offered
    • 15.1.2.3 Recent developments
      • 15.1.2.3.1 Deals
    • 15.1.2.4 MnM view
      • 15.1.2.4.1 Key strengths
      • 15.1.2.4.2 Strategic choices
      • 15.1.2.4.3 Weaknesses & competitive threats
  • 15.1.3 KONINKLIJKE PHILIPS N.V.
    • 15.1.3.1 Business overview
    • 15.1.3.2 Products/Services offered
    • 15.1.3.3 Recent developments
      • 15.1.3.3.1 Deals
    • 15.1.3.4 MnM view
      • 15.1.3.4.1 Key strengths
      • 15.1.3.4.2 Strategic choices
      • 15.1.3.4.3 Weaknesses & competitive threats
  • 15.1.4 DASSAULT SYSTEMES
    • 15.1.4.1 Business overview
    • 15.1.4.2 Products/Services offered
    • 15.1.4.3 Recent developments
      • 15.1.4.3.1 Product/Service launches & enhancements
      • 15.1.4.3.2 Deals
    • 15.1.4.4 MnM view
      • 15.1.4.4.1 Key strengths
      • 15.1.4.4.2 Strategic choices
      • 15.1.4.4.3 Weaknesses & competitive threats
  • 15.1.5 AMAZON WEB SERVICES, INC.
    • 15.1.5.1 Business overview
    • 15.1.5.2 Products/Services offered
    • 15.1.5.3 Recent developments
      • 15.1.5.3.1 Product/Service launches & enhancements
      • 15.1.5.3.2 Deals
    • 15.1.5.4 MnM view
      • 15.1.5.4.1 Key strengths
      • 15.1.5.4.2 Strategic choices
      • 15.1.5.4.3 Weaknesses & competitive threats
  • 15.1.6 GE HEALTHCARE
    • 15.1.6.1 Business overview
    • 15.1.6.2 Products/Services offered
    • 15.1.6.3 Recent developments
      • 15.1.6.3.1 Deals
  • 15.1.7 ORACLE
    • 15.1.7.1 Business overview
    • 15.1.7.2 Products/Services offered
    • 15.1.7.3 Recent developments
      • 15.1.7.3.1 Deals
  • 15.1.8 IBM
    • 15.1.8.1 Business overview
    • 15.1.8.2 Products/Services offered
    • 15.1.8.3 Recent developments
      • 15.1.8.3.1 Deals
  • 15.1.9 PTC
    • 15.1.9.1 Business overview
    • 15.1.9.2 Products/Services offered
    • 15.1.9.3 Recent developments
      • 15.1.9.3.1 Deals
  • 15.1.10 SAP
    • 15.1.10.1 Business overview
    • 15.1.10.2 Products/Services offered
    • 15.1.10.3 Recent developments
      • 15.1.10.3.1 Deals
      • 15.1.10.3.2 Other developments
  • 15.1.11 ATOS SE
    • 15.1.11.1 Business overview
    • 15.1.11.2 Products/Services offered
    • 15.1.11.3 Recent developments
      • 15.1.11.3.1 Deals
  • 15.1.12 NVIDIA CORPORATION
    • 15.1.12.1 Business overview
    • 15.1.12.2 Products/Services offered
    • 15.1.12.3 Recent developments
      • 15.1.12.3.1 Product/Service launches & enhancements
      • 15.1.12.3.2 Deals
  • 15.1.13 ANSYS INC.
    • 15.1.13.1 Business overview
    • 15.1.13.2 Products/Services offered
    • 15.1.13.3 Recent developments
      • 15.1.13.3.1 Product/Service launches & enhancements
      • 15.1.13.3.2 Deals
  • 15.1.14 FASTSTREAM TECHNOLOGIES
    • 15.1.14.1 Business overview
    • 15.1.14.2 Products/Services offered
  • 15.1.15 RESCALE, INC.
    • 15.1.15.1 Business overview
    • 15.1.15.2 Products/Services offered
      • 15.1.15.2.1 Other developments
• 15.2 OTHER PLAYERS
  • 15.2.1 TWIN HEALTH
  • 15.2.2 VERTO HEALTH
  • 15.2.3 QBIO
  • 15.2.4 THOUGHTWIRE
  • 15.2.5 SIM&CURE
  • 15.2.6 OWKIN, INC
  • 15.2.7 NUREA
  • 15.2.8 UNLEARN.AI, INC.
  • 15.2.9 VIRTONOMY GMBH
  • 15.2.10 PREDISURGE

16 RESEARCH METHODOLOGY

• 16.1 RESEARCH APPROACH
  • 16.1.1 SECONDARY RESEARCH
    • 16.1.1.1 Key data from secondary sources
  • 16.1.2 PRIMARY RESEARCH
    • 16.1.2.1 Key data from primary sources
    • 16.1.2.2 Breakdown of primaries
    • 16.1.2.3 Insights from primary experts
• 16.2 RESEARCH METHODOLOGY DESIGN
• 16.3 MARKET SIZE ESTIMATION
• 16.4 MARKET BREAKDOWN DATA TRIANGULATION
• 16.5 MARKET SHARE ESTIMATION
• 16.6 STUDY ASSUMPTIONS
• 16.7 RESEARCH LIMITATIONS
  • 16.7.1 METHODOLOGY-RELATED LIMITATIONS
  • 16.7.2 SCOPE-RELATED LIMITATIONS
• 16.8 RISK ASSESSMENT

17 APPENDIX

• 17.1 DISCUSSION GUIDE
• 17.2 KNOWLEDGESTORE: MARKETSANDMARKETS' SUBSCRIPTION PORTAL
• 17.3 CUSTOMIZATION OPTIONS
• 17.4 RELATED REPORTS
• 17.5 AUTHOR DETAILS