Artificial Intelligence Ai In Medical Diagnostics Market
Artificial Intelligence (AI) in Medical Diagnostics Market Forecasts to 2030 - Global Analysis By Component (Services, Software and Other Components), Specialty (Obstetrics & Gynecology (OB-GYN), Chest & Lung, Oncology, Brain & Neurological, Radiology and Other Specialties), Modality, Artificial Intelligence (AI) Technology, Application, End User and By Geography
Years Covered |
2021-2030 |
Estimated Year Value (2023) |
US $1.3 BN |
Projected Year Value (2030) |
US $10.5 BN |
CAGR (2023 - 2030) |
34.2% |
Regions Covered |
North America, Europe, Asia Pacific, South America, and Middle East & Africa |
Countries Covered |
US, Canada, Mexico, Germany, UK, Italy, France, Spain, Japan, China, India, Australia, New Zealand, South Korea, Rest of Asia Pacific, South America, Argentina, Brazil, Chile, Middle East & Africa, Saudi Arabia, UAE, Qatar, and South Africa |
Largest Market |
Asia Pacific |
Highest Growing Market |
Asia Pacific |
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
• Computerized Tomography (CT) Scan
• X-ray
• Other Modalities
Artificial Intelligence (AI) Technologies Covered:
• Context-Aware Computing
• Machine Learning
• Computer Vision
• Other Artificial Intelligence (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
o US
o Canada
o Mexico
• Europe
o Germany
o UK
o Italy
o France
o Spain
o Rest of Europe
• Asia Pacific
o Japan
o China
o India
o Australia
o New Zealand
o South Korea
o Rest of Asia Pacific
• South America
o Argentina
o Brazil
o Chile
o Rest of South America
• Middle East & Africa
o Saudi Arabia
o UAE
o Qatar
o South Africa
o 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
o Comprehensive profiling of additional market players (up to 3)
o SWOT Analysis of key players (up to 3)
• Regional Segmentation
o 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 Computerized Tomography (CT) Scan
7.4 X-ray
7.5 Other Modalities
8 Global Artificial Intelligence (AI) in Medical Diagnostics Market, By Artificial Intelligence (AI) Technology
8.1 Introduction
8.2 Context-Aware Computing
8.3 Machine Learning
8.4 Computer Vision
8.5 Other Artificial Intelligence (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
List of Tables
1 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Region (2021-2030) ($MN)
2 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Component (2021-2030) ($MN)
3 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Services (2021-2030) ($MN)
4 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Software (2021-2030) ($MN)
5 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Other Components (2021-2030) ($MN)
6 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Specialty (2021-2030) ($MN)
7 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Obstetrics & Gynecology (OB-GYN) (2021-2030) ($MN)
8 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Chest & Lung (2021-2030) ($MN)
9 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Oncology (2021-2030) ($MN)
10 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Brain & Neurological (2021-2030) ($MN)
11 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Radiology (2021-2030) ($MN)
12 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Other Specialties (2021-2030) ($MN)
13 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Modality (2021-2030) ($MN)
14 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Ultrasound (2021-2030) ($MN)
15 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Computerized Tomography (CT) Scan (2021-2030) ($MN)
16 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By X-ray (2021-2030) ($MN)
17 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Other Modalities (2021-2030) ($MN)
18 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Artificial Intelligence (AI) Technology (2021-2030) ($MN)
19 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Context-Aware Computing (2021-2030) ($MN)
20 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Machine Learning (2021-2030) ($MN)
21 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Computer Vision (2021-2030) ($MN)
22 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Other Artificial Intelligence (AI) Technologies (2021-2030) ($MN)
23 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Application (2021-2030) ($MN)
24 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By In Vitro Diagnostics (2021-2030) ($MN)
25 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By In Vivo Diagnostics (2021-2030) ($MN)
26 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Clinical Decision Support (2021-2030) ($MN)
27 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Computer-Aided Diagnosis (2021-2030) ($MN)
28 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Other Applications (2021-2030) ($MN)
29 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By End User (2021-2030) ($MN)
30 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Diagnostic Imaging Centers (2021-2030) ($MN)
31 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Hospitals (2021-2030) ($MN)
32 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Diagnostic Laboratories (2021-2030) ($MN)
33 Global Artificial Intelligence (AI) in Medical Diagnostics Market Outlook, By Other End Users (2021-2030) ($MN)
Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.
List of Figures
RESEARCH METHODOLOGY
We at ‘Stratistics’ opt for an extensive research approach which involves data mining, data validation, and data analysis. The various research sources include in-house repository, secondary research, competitor’s sources, social media research, client internal data, and primary research.
Our team of analysts prefers the most reliable and authenticated data sources in order to perform the comprehensive literature search. With access to most of the authenticated data bases our team highly considers the best mix of information through various sources to obtain extensive and accurate analysis.
Each report takes an average time of a month and a team of 4 industry analysts. The time may vary depending on the scope and data availability of the desired market report. The various parameters used in the market assessment are standardized in order to enhance the data accuracy.
Data Mining
The data is collected from several authenticated, reliable, paid and unpaid sources and is filtered depending on the scope & objective of the research. Our reports repository acts as an added advantage in this procedure. Data gathering from the raw material suppliers, distributors and the manufacturers is performed on a regular basis, this helps in the comprehensive understanding of the products value chain. Apart from the above mentioned sources the data is also collected from the industry consultants to ensure the objective of the study is in the right direction.
Market trends such as technological advancements, regulatory affairs, market dynamics (Drivers, Restraints, Opportunities and Challenges) are obtained from scientific journals, market related national & international associations and organizations.
Data Analysis
From the data that is collected depending on the scope & objective of the research the data is subjected for the analysis. The critical steps that we follow for the data analysis include:
- Product Lifecycle Analysis
- Competitor analysis
- Risk analysis
- Porters Analysis
- PESTEL Analysis
- SWOT Analysis
The data engineering is performed by the core industry experts considering both the Marketing Mix Modeling and the Demand Forecasting. The marketing mix modeling makes use of multiple-regression techniques to predict the optimal mix of marketing variables. Regression factor is based on a number of variables and how they relate to an outcome such as sales or profits.
Data Validation
The data validation is performed by the exhaustive primary research from the expert interviews. This includes telephonic interviews, focus groups, face to face interviews, and questionnaires to validate our research from all aspects. The industry experts we approach come from the leading firms, involved in the supply chain ranging from the suppliers, distributors to the manufacturers and consumers so as to ensure an unbiased analysis.
We are in touch with more than 15,000 industry experts with the right mix of consultants, CEO's, presidents, vice presidents, managers, experts from both supply side and demand side, executives and so on.
The data validation involves the primary research from the industry experts belonging to:
- Leading Companies
- Suppliers & Distributors
- Manufacturers
- Consumers
- Industry/Strategic Consultants
Apart from the data validation the primary research also helps in performing the fill gap research, i.e. providing solutions for the unmet needs of the research which helps in enhancing the reports quality.
For more details about research methodology, kindly write to us at info@strategymrc.com
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