세계의 의료 진단용 인공지능(AI) 시장 예측(-2030년) : 구성요소별, 전문 분야별, 모달리티별, AI 기술별, 용도별, 최종사용자별, 지역별 분석

According to Stratistics MRC, the Global Artificial Intelligence (AI) in Medical Diagnostics Market is accounted for $1.3 billion in 2023 and is expected to reach $10.5 billion by 2030 growing at a CAGR of 34.2% during the forecast period. By supporting healthcare professionals in making accurate and timely treatment decisions for their patients, artificial intelligence (AI) in medical diagnostics has the potential to improve access to and the cost of healthcare. It takes years of medical education and a lot of time to diagnose a condition accurately. The application of AI to medical diagnosis has demonstrated its ability to provide precise diagnoses, support clinical decisions, and improve healthcare professionals judgment.

According to the data by the World Bank, USD 1,111.082 was spent per capita on healthcare in 2018.

Market Dynamics:

Driver:

Expansion of healthcare data availability

Electronic health records (EHRs), medical imaging data, and genomic data, which have become readily available in huge amounts, have made it possible to develop and validate AI models. Moreover, the collection and use of these data have been made easier by the digitization of healthcare data and the deployment of interoperable systems, enabling AI algorithms to learn from a variety of patient groups and increase diagnostic precision.

Restraint:

Budgetary limitations

The main obstacle facing healthcare companies is funding, particularly in developing nations where it is difficult to prioritize IT funds over medical equipment. Particularly in nations where the reimbursement situation is unfavorable, the high cost of imaging equipment and the implementation and licensing expenses of AI software are the main issues limiting market growth. However, due to high installation and maintenance costs, for instance, the majority of healthcare facilities in developing nations cannot afford AI solutions. The adoption of innovative or cutting-edge systems is being hampered by this factor.

Opportunity:

Availability of big data

Big data (huge and complex data) is produced at various phases of the care delivery process as a result of the industry's growing digitization and adoption of information systems. Big data in the field of medical diagnostics includes, among other things, information generated from clickstream and web and social media interactions, readings from medical devices like sensors, ECGs, X-rays, and other billing records, as well as biometric data. Additionally, with the increasing acceptance of EHRs, digitized laboratory slides, and high-resolution radiological images among medical professionals over the past few years, big data and analytical solutions have become exponentially more advanced and widely used.

Threat:

Lack of interpretability and transparency

Deep learning models in particular, which are used in AI algorithms, can be complex and challenging to understand. Healthcare practitioners might discover it difficult to trust and comprehend the logic behind AI-generated diagnoses due to the ambiguity of how AI comes to its conclusions. However, AI models must be accessible and measurable in order to be accepted and recognized by healthcare professionals.

COVID-19 Impact:

The COVID-19 pandemic epidemic had a negative impact on the worldwide healthcare industry. The COVID-19 infection rate increased dramatically, placing an enormous burden on the global health system. Patients with COVID-19 typically experience lung problems. Therefore, to determine the severity of the disease in COVID-19 instances, cardiothoracic imaging is a standard diagnostic procedure. In 2020, the number of studies utilizing AI to diagnose COVID-19 rapidly increased.

The software segment is expected to be the largest during the forecast period

Due to the rising demand for AI-based software in diagnostics to provide an accurate diagnosis in a timely manner, the rapid development of new AI algorithms and new software approvals, and the applications of AI-based software in a variety of fields, including radiology, cardiology, neurology, gynecology, and ophthalmology, among others, the software segment held the largest share over the projection period. Additionally, despite the challenges of having a shortage of employees and the need to deal with rising imaging scan volumes, software solutions give healthcare providers a competitive edge over their rivals.

The hospitals segment is expected to have the highest CAGR during the forecast period

Due to factors like the benefits of implementing AI-based solutions to automate diagnosis and reduce workload in hospitals, the rise in the number of patients undergoing diagnostic procedures, the expanding demand for early disease detection, and the shortage of medical specialists, the hospital segment is predicted to experience profitable growth throughout the forecast period. Furthermore, there is a growing need for AI-based medical technologies in hospitals that are used for diagnosis in order to reduce complexity and errors, save money and time, and be performed quickly and easily by professionals and skilled workers. Many hospitals have partnerships with digital firms to offer cloud-based AI services and solutions to their patients. By using these solutions in their daily operations, the hospitals will increase their productivity and efficiency.

Region with largest share:

Owing to the rising incidence of various chronic and infectious diseases, the rising number of AI-based startups, particularly in China and India, and the enormous potential of AI in filling the gap in the region's healthcare infrastructure, Asia Pacific is predicted to hold the largest share over the extrapolated period. Moreover, the availability of equity investments and start-up incubation has an impact on the development of regional markets. The region's rising aging population and higher prevalence of acute and chronic illnesses are both expected to boost market expansion in the region.

Region with highest CAGR:

Due to factors including the increasing demand for accurate and prompt diagnosis and the rising frequency of chronic diseases owing to the aging population worldwide, Asia-Pacific is expected to have profitable growth. Additionally, the benefits offered by AI-based solutions in the diagnosis of different neurological diseases, such as helping radiologists interpret medical images to make a rapid and precise diagnosis, reducing noise in medical images, and producing high-quality images from lower doses of radiation, are enhancing regional growth.

Key players in the market:

Some of the key players in Artificial Intelligence (AI) in Medical Diagnostics market include: Orthofix Medical Inc., NuVasive, Inc., Baxter International Inc, OrthoPediatrics Corp., Arthrex, Inc, AlloSource, Wright Medical Group N.V., Stryker Corporation, GreenBone Ortho, Zimmer Biomet Holdings, Inc, Smith & Nephew Plc, GRAFTYS, Medtronic Plc, Bioventus Inc, Musculoskeletal Transplant Foundation, SeaSpine, GreenBone Ortho.

Key Developments:

In September 2023, IBM commits to train 2 million in artificial intelligence in three years, with a Focus on Underrepresented Communities. To achieve this goal at a global scale, IBM is expanding AI education collaborations with universities globally, collaborating with partners to deliver AI training to adult learners, and launching new generative AI coursework through IBM SkillsBuild. This will expand upon IBM's existing programs and career-building platforms to offer enhanced access to AI education and in-demand technical roles.

In September 2023, IBM is offering a robust FSMA 204 traceability and compliance management solution capable of supporting the needs of the industry's largest enterprises and suppliers of all sizes. The solution combines the scalability and interoperability of the IBM Sterling Supply Chain Intelligence Suite and the IBM Food Trust Network with iFoodDS' traceability applications and innovative food industry, regulatory, and technical expertise.

Components Covered:

• Services
• Software
• Other Components

Specialties Covered:

• Obstetrics & Gynecology (OB-GYN)
• Chest & Lung
• Oncology
• Brain & Neurological
• Radiology
• Other Specialties

Modalities Covered:

• Ultrasound
• CT Scan
• X-ray
• Other Modalities

AI Technologies Covered:

• Context-Aware Computing
• Machine Learning
• Computer Vision
• Other AI Technologies

Applications Covered:

• In Vitro Diagnostics
• In Vivo Diagnostics
• Clinical Decision Support
• Computer-Aided Diagnosis
• Other Applications

End Users Covered:

• Diagnostic Imaging Centers
• Hospitals
• 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 2021, 2022, 2023, 2026, and 2030
• 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 Application Analysis
• 3.7 End User Analysis
• 3.8 Emerging Markets
• 3.9 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 Artificial Intelligence (AI) in Medical Diagnostics Market, By Component

• 5.1 Introduction
• 5.2 Services
• 5.3 Software
• 5.4 Other Components

6 Global Artificial Intelligence (AI) in Medical Diagnostics Market, By Specialty

• 6.1 Introduction
• 6.2 Obstetrics & Gynecology (OB-GYN)
• 6.3 Chest & Lung
• 6.4 Oncology
• 6.5 Brain & Neurological
• 6.6 Radiology
• 6.7 Other Specialties

7 Global Artificial Intelligence (AI) in Medical Diagnostics Market, By Modality

• 7.1 Introduction
• 7.2 Ultrasound
• 7.3 CT Scan
• 7.4 X-ray
• 7.5 Other Modalities

8 Global Artificial Intelligence (AI) in Medical Diagnostics Market, By AI Technology

• 8.1 Introduction
• 8.2 Context-Aware Computing
• 8.3 Machine Learning
• 8.4 Computer Vision
• 8.5 Other AI Technologies

9 Global Artificial Intelligence (AI) in Medical Diagnostics Market, By Application

• 9.1 Introduction
• 9.2 In Vitro Diagnostics
• 9.3 In Vivo Diagnostics
• 9.4 Clinical Decision Support
• 9.5 Computer-Aided Diagnosis
• 9.6 Other Applications

10 Global Artificial Intelligence (AI) in Medical Diagnostics Market, By End User

• 10.1 Introduction
• 10.2 Diagnostic Imaging Centers
• 10.3 Hospitals
• 10.4 Diagnostic Laboratories
• 10.5 Other End Users

11 Global Artificial Intelligence (AI) in Medical Diagnostics Market, By Geography

• 11.1 Introduction
• 11.2 North America
  • 11.2.1 US
  • 11.2.2 Canada
  • 11.2.3 Mexico
• 11.3 Europe
  • 11.3.1 Germany
  • 11.3.2 UK
  • 11.3.3 Italy
  • 11.3.4 France
  • 11.3.5 Spain
  • 11.3.6 Rest of Europe
• 11.4 Asia Pacific
  • 11.4.1 Japan
  • 11.4.2 China
  • 11.4.3 India
  • 11.4.4 Australia
  • 11.4.5 New Zealand
  • 11.4.6 South Korea
  • 11.4.7 Rest of Asia Pacific
• 11.5 South America
  • 11.5.1 Argentina
  • 11.5.2 Brazil
  • 11.5.3 Chile
  • 11.5.4 Rest of South America
• 11.6 Middle East & Africa
  • 11.6.1 Saudi Arabia
  • 11.6.2 UAE
  • 11.6.3 Qatar
  • 11.6.4 South Africa
  • 11.6.5 Rest of Middle East & Africa

12 Key Developments

• 12.1 Agreements, Partnerships, Collaborations and Joint Ventures
• 12.2 Acquisitions & Mergers
• 12.3 New Product Launch
• 12.4 Expansions
• 12.5 Other Key Strategies

13 Company Profiling

• 13.1 Agfa Healthcare
• 13.2 Digital Diagnostics Inc.
• 13.3 GE Healthcare
• 13.4 Google Inc
• 13.5 HeartFlow, Inc.
• 13.6 IBM Corporation
• 13.7 Imagen Technologies
• 13.8 Intel Corporation
• 13.9 International Business Machines Corporation
• 13.10 Koninklijke Philips N.V
• 13.11 Microsoft Corporation
• 13.12 NovaSignal Corporation
• 13.13 Riverain Technologies
• 13.14 Siemens Healthineers AG
• 13.15 Zebra Medical Vision Inc