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The global AI in Diagnostics market was valued at USD 336.0 million in 2019 and is expected to grow at a CAGR of 35.5% over the forecast period. The growing lack of public health professionals and increasing Artificial Intelligence (AI) technologies have been implemented largely as a part of the move to value-based care programmes. In 2018, on a trial basis, the NHS deployed AI-based chatbots to reduce the burden on the emergency triage process. The introduction of this AI platform is expected to fuel clinical diagnosis development by extending healthcare facilities internationally, resulting in increased patient protection, outcome monitoring and data collection.
Key players serving the global market include Aidoc, AliveCor, GE Healthcare, Imagen Technologies, Vuno Inc., IDx Technologies Inc., Siemens Healthcare GmbH, Neural Analytics, Riverain Technologies, Zebra Medical Vision, among other prominent players.
Key segments of the global AI in Diagnostics market
Component Overview, 2018-2028 (USD Million)
Application Overview, 2018-2028 (USD Million)
Regional Overview, 2018-2028 (USD Million)
Reasons for the study
What does the report include?
Who should buy this report?
Consultants, analysts, researchers, and academicians looking for insights shaping the global AI in Diagnostics market
The implementation of artificial intelligence in diagnostic imaging and medical diagnostics is one of the most prospective areas of health innovation. The research offers insights into opportunities, knowledge, demand and developments in categories such as healthcare machine learning, AI incorporation into radiology, and more. Applications for artificial intelligence range from image collection, processing to assisted reporting, follow-up strategy, storing of images, data mining, among others. The study provides a balance for radiologists in the contemporary medical world between AI risks and opportunities.
The increasing quantity of data being processed can affect how images are interpreted by radiologists, i.e. from inference to identification and interpretation. When radiologists examine so many images in a day, the odds of error rise, whereas a radiologist is reduced to a simple "data analyst." AI has the ability to eliminate much of the repetitive diagnosis, characterization, and quantification functions typically conducted by radiologists using cognitive ability and to combine electronic health records with data mining in the process.
The introduction of this AI platform is expected to improve the development of clinical diagnosis by ramping up healthcare facilities internationally, leading to improved patient protection, result monitoring, and data collection. For example, in the healthcare sector, IBM's Watson goes head to head with general intelligence and has demonstrated to have tremendous potential. This website has helped to identify a woman diagnosed from leukaemia. Google entered into an agreement with the UK's NHS in 2016 to evaluate medical photographs obtained for early cancer diagnosis from patients.
The global AI in Diagnostics market has been bifurcated based on component, application and region. In terms of Component the market is divided into Software, Hardware, Services. On the basis of application, the segment is divided into Cardiology, Oncology, Pathology, Radiology, Chest and Lung, Neurology, and Others.
During the forecast era, software segment has emerged as the leading business area. This major proportion is due primarily to the advancement of AI-based apps for detection in healthcare. One of the main drivers driving the sector is the growing demand for AI-powered and cloud-based enhanced diagnostic applications that help to improve diagnostic accuracy when reading a people's clinical images. Neurology had a market share of over 20.0 percent in 2019, while radiology is projected to be the quickest increasing market during the forecast period due to the increasing growth of AI-based medical imaging applications. Neurology accounts for the highest number of regulatory licenses, accounting for about 19 % of the total medical diagnostics network dependent on AI.
Based on regions, the global AI in Diagnostics market is segmented into North America, Europe, Asia Pacific, Central and South America and Middle East & Africa. Emerging markets such as APAC are giving companies major growth prospects in the demand for the Industry’s in coming years.
North America holds the largest share of market this is due to the increasing acceptance in clinical diagnosis of medical IT solutions, the advent of a very well-established healthcare industry, and high financing for AI-based diagnostic software growth. In North America, the U.S. leads the artificial intelligence industry in diagnosis and treatment. This can be due to the growing production and introduction of advanced and sophisticated medical diagnostic software and the emergence in the nation of a lot of players working across sectors, such as smartphone and network operations.
The global AI in Diagnostics market was valued at USD 336.0 million in 2019 and is expected to grow at a CAGR of 35.5% over the forecast period. The growing lack of public health professionals and increasing Artificial Intelligence (AI) technologies have been implemented largely as a part of the move to value-based care programmes. In 2018, on a trial basis, the NHS deployed AI-based chatbots to reduce the burden on the emergency triage process. The introduction of this AI platform is expected to fuel clinical diagnosis development by extending healthcare facilities internationally, resulting in increased patient protection, outcome monitoring and data collection.
Key players serving the global market include Aidoc, AliveCor, GE Healthcare, Imagen Technologies, Vuno Inc., IDx Technologies Inc., Siemens Healthcare GmbH, Neural Analytics, Riverain Technologies, Zebra Medical Vision, among other prominent players.
Key segments of the global AI in Diagnostics market
Component Overview, 2018-2028 (USD Million)
Application Overview, 2018-2028 (USD Million)
Regional Overview, 2018-2028 (USD Million)
Reasons for the study
What does the report include?
Who should buy this report?
Consultants, analysts, researchers, and academicians looking for insights shaping the global AI in Diagnostics market
Chapter 1. Introduction
1.1. Introduction to the Study
1.2. Market Definition and Scope
1.3. Units, Currency, Conversions and Years Considered
1.4. Key Stakeholders
1.5. Key Questions Answered
Chapter 2. Research Methodology
2.1. Introduction
2.2. Data Capture Sources
2.3. Primary Sources
2.4. Secondary Sources
2.5. Market Size Estimation
2.6. Market Forecast
2.7. Data Triangulation
2.8. Assumptions and Limitations
Chapter 3. Market Outlook
3.1. Introduction
3.2. Macroeconomic Indicators
3.3. Market Dynamics
3.3.1. Drivers
3.3.2. Restraints
3.3.3. Opportunities
3.3.4. Challenges
3.4. Porter’s Five Forces Analysis
3.5. COVID-19 Impact Analysis
Chapter 4. Global AI in Diagnostics Market by Component, 2018-2028 (USD Million)
4.1. Software
4.2. Hardware
4.3. Services
Chapter 5. Global AI in Diagnostics Market by application, 2018-2028 (USD Million)
5.1. Cardiology
5.2. Oncology
5.3. Pathology
5.4. Radiology
5.5. Chest and Lung
5.6. Neurology
5.7. Others
Chapter 6. Global AI in Diagnostics Market by Region, 2018-2028 (USD Million)
6.1. North America
6.1.1. U.S.
6.1.2. Canada
6.2. Europe
6.2.1. Germany
6.2.2. UK
6.2.3. France
6.2.4. Spain
6.2.5. Rest of Europe
6.3. Asia Pacific
6.3.1. Japan
6.3.2. China
6.3.3. India
6.3.4. Rest of Asia Pacific
6.4. Central and South America
6.5. Middle East and Africa
Chapter 7. Company Profiles
7.1. Aidoc
7.1.1. Overview
7.1.2. Industrys and Services Portfolio
7.1.3. Recent Initiatives
7.1.4. Company Financials
7.2. Zebra Medical Vision
7.2.1. Overview
7.2.2. Industrys and Services Portfolio
7.2.3. Recent Initiatives
7.2.4. Company Financials
7.3. Riverain Technologies
7.3.1. Overview
7.3.2. Industrys and Services Portfolio
7.3.3. Recent Initiatives
7.3.4. Company Financials
7.4. Siemens Healthcare GmbH
7.4.1. Overview
7.4.2. Industrys and Services Portfolio
7.4.3. Recent Initiatives
7.4.4. Company Financials
7.5. Neural Analytics
7.5.1. Overview
7.5.2. Industrys and Services Portfolio
7.5.3. Recent Initiatives
7.5.4. Company Financials
7.6. IDx Technologies Inc.
7.6.1. Overview
7.6.2. Industrys and Services Portfolio
7.6.3. Recent Initiatives
7.6.4. Company Financials
7.7. Vuno Inc.
7.7.1. Overview
7.7.2. Industrys and Services Portfolio
7.7.3. Recent Initiatives
7.7.4. Company Financials
7.8. Imagen Technologies
7.8.1. Overview
7.8.2. Industrys and Services Portfolio
7.8.3. Recent Initiatives
7.8.4. Company Financials
7.9. GE Healthcare
7.9.1. Overview
7.9.2. Industrys and Services Portfolio
7.9.3. Recent Initiatives
7.9.4. Company Financials
7.10. AliveCor
7.10.1. Overview
7.10.2. Industrys and Services Portfolio
7.10.3. Recent Initiatives
7.10.4. Company Financials
Chapter 8. Appendix
8.1. Primary Research Approach
8.1.1. Primary Interview Participants
8.1.2. Primary Interview Summary
8.2. Questionnaire
8.3. Related Reports
8.3.1. Published
8.3.2. Upcoming