The Artificial Intelligence in Diagnostics Market was valued at USD 1172.6 million in 2023 and is project to reach USD 6341.68 million by 2031 with a growing CAGR of 23.49% during the forecast period 2024-2031.
One of the most significant scientific advances in medicine to date is artificial intelligence in healthcare. A crucial aspect contributing to the sector's growth is the involvement of multiple start-ups in the development of AI-driven imaging and diagnostic products.Image collecting, processing, aided reporting, follow-up, data storage, data mining, and other artificial intelligence applications are all available. The paper strikes a balance between AI's risks and radiologists' prospects in today's medical world. Machine learning blends computational models and algorithms with artificial neural networks to mimic the brain's biological neural network architecture (ANNs). Deep learning has a better success rate than traditional machine learning in terms of output.
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The increasing amount of data to be processed has the potential to change how radiologists evaluate images, affecting everything from inference to identification and explanation. When radiologists process too many images in a day, the chances of error increase, and the radiologist's role is limited to that of a pure image analyst. Other physicians or specialists should be entrusted with the clinical interpretation of the data. In other words, if radiologists don't have time for professional judgement, or if there aren't enough radiologists in places like India or Eastern Europe, or if there aren't enough radiologists in Africa, the final evaluation of radiological testing will be left to non-medical imaging experts.
Increasing Adoption of Artificial Intelligence in the Healthcare Sector
Growing Investment in Healthcare Sector
Improving computing power and declining hardware cost
In recent years, the growing adoption of AI has become a new growth engine for semiconductor chipset manufacturers. Nvidia, AMD, Intel, Qualcomm, Huawei, and Samsung, among others, have made major investments in this field to produce chipsets that are compatible with AI-based technologies and solutions. Application-specific integrated circuits (ASICs) and field-programmable gate arrays (FPGAs) are being developed for AI applications in addition to CPUs and GPUs. Google, for example, has developed a new ASIC called the tensor processing unit (TPU).
One of the important criteria for processing AI algorithms is a compute-intensive chipset; the faster the chipset, the faster it can process the data required to develop an AI system. Currently, AI chipsets are primarily used in data centres and high-end servers because end PCs are unable to handle such large workloads and lack the necessary power and time. Nvidia offers a variety of GPUs with different GPU memory bandwidth options depending on the application. The GeForce GTX Titan X, for example, has a memory bandwidth of 336.5 GB/s and is primarily utilised in desktops, but the Tesla V100 16 GB has a memory bandwidth of 900 GB/s and is primarily used in AI applications.
Reluctance among medical practitioners to adopt AI-based technologies
With the rapid advancement of digital health and mobile health technology, healthcare providers can now support patients with unique treatment options. Doctors can use AI technologies to help them diagnose and treat patients more effectively. Doctors, on the other hand, have shown a reluctance to adopt new technologies. For example, there is a widespread belief among medical professionals that AI will eventually replace doctors. Doctors and practitioners feel that qualities like empathy and persuasion are human abilities, and that technological advancements cannot totally eliminate the need for a doctor.
Increasing focus on developing human-aware AI systems
During the growth of AI technologies, the actual projections intended to make these technologies human-aware, i.e., constructing models with human-like cognitive properties. The inventors of AI machines, on the other hand, face a hurdle in constructing interactive and scalable machines. Furthermore, as human influence with AI approaches has increased, new research challenges have emerged, such as interpretation and presentation issues with automating parts and intelligent control of crowdsourcing parts. The difficulties that AI computers encounter in understanding human input, such as knowledge and particular commands, are referred to as interpretation issues.
Issues with delivering the AI system's output and feedback are among the presentation concerns. Because of the complexity of the output, feedback can be interpreted in a variety of ways. To avoid any ambiguity, the output must be provided exactly as it was intended. This can be difficult if the intended user does not have a strong understanding of the technology. As a result, the development of human-aware AI systems remains the most promising avenue for AI researchers.
Requirement of High Initial Investment
Concerns regarding data privacy
In the field of medicine, AI has a number of applications. However, due to data privacy issues, AI use in the sector is limited. In several nations, federal regulations protect patient health data, and any compromise or failure to maintain its integrity can result in legal and financial penalties. Because AI for patient care necessitates access to a variety of health information, AI-based technologies must follow all data security procedures put forth by governments and regulatory agencies. This is a difficult undertaking because most AI platforms are consolidated and require significant computational capacity, necessitating the storage of patient data, or portions of it, in a vendor's data centre.
Many companies are developing software solutions for a variety of healthcare applications, which is a crucial reason in the software segment's growth. Strong demand among software developers (particularly at medical institutions and colleges) and expanding AI applications in the healthcare industry are two major drivers driving the AI platform's rise in the software market. Google AI Platform, TensorFlow, Microsoft Azure, Premonition, Watson Studio, Lumiata, and Infrrd are some of the top AI platforms.
The Russia-Ukraine war is negatively impacting the global Artificial Intelligence (AI) in Diagnostics market, with intense effects expected for years to come. While the immediate impact is a slowdown in AI adoption in the war-torn region, the long-term consequences are more nuanced. On the one hand, the war has diverted crucial resources away from healthcare budgets in Ukraine and Russia, potentially stalling AI investments in these markets. A 2023 report by the Center for Strategic and International Studies (CSIS) estimated a 20% decrease in healthcare spending in Ukraine due to the war. This translates to a potential decline in AI diagnostics adoption, which typically requires significant upfront costs. However, the war has also spurred advancements in AI-powered medical diagnostics for battlefield medicine and remote patient monitoring. The urgent need for efficient and accurate medical diagnosis in resource-constrained environments is driving innovation in AI-powered triage systems and remote analysis tools. For instance, AI-based image analysis algorithms are being developed to analyse battlefield injuries and prioritize critical cases. This real-world testing ground for AI diagnostics could lead to breakthroughs that benefit the global healthcare sector in the long run. Overall, the war's impact on the AI in Diagnostics market is a mixed bag. While near-term spending in affected regions might decline, the war's demands are also accelerating innovation in specific areas of AI diagnostics. The net effect on the global market will depend on the war's duration and the pace of technological advancements spurred by wartime needs.
Startups and smaller companies, the backbone of AI innovation, may struggle to secure venture capital or face budget cuts from existing investors. This could stifle the development of new AI-powered diagnostic tools and delay their entry into the market. Secondly, healthcare institutions, facing potential budget constraints, might become more hesitant to adopt these new technologies. The high upfront costs of implementing AI systems, coupled with uncertainties about their long-term return on investment (ROI), could lead to a wait-and-see approach. This could hamper the overall market growth rate. However, the slowdown might also present an opportunity for consolidation. Established players with stronger financial resources could acquire smaller companies with promising AI technology, accelerating their own development efforts. Additionally, the potential cost-saving benefits of AI, such as improved diagnostic accuracy and reduced healthcare spending, might become even more attractive during an economic downturn.
Key Market Segmentation
Software
Hardware
Services
Software currently holds the biggest share, exceeding 45% of the market in 2023. It's also projected to see the fastest growth, with a compound annual growth rate (CAGR) of 25.7% expected from 2024 to 2031. This surge is driven by the increasing demand for AI tools that enable faster and more accurate diagnoses. With a growing number of people being diagnosed with various diseases, the need for advanced AI solutions in diagnostics is on the rise.
Cardiology
Oncology
Pathology
Radiology
Chest and Lung
Neurology
Others
Neurology takes the top spot with over 24% market share due to rising neurological disorders. Value-based care adoption and advanced AI algorithms fuel this segment. Radiology is the fastest growing, with a projected fastest growth of 27.3% due to the demand for faster, cheaper, and more accurate analysis. AI's integration with EHRs and radiology findings helps diagnose diseases earlier, leading to better treatment.
Regional Analysis:
North America currently holds the largest market share, at around 40%, driven by factors like strong government support for AI research, a high concentration of leading healthcare institutions, and a growing emphasis on advanced diagnostics. Europe follows closely at nearly 30%, forced by a strong healthcare infrastructure and increasing investments in AI-powered solutions. Asia Pacific is a region to watch, with a projected CAGR exceeding 25% due to a expanding patient population, rising healthcare expenditure, and government initiatives promoting AI adoption. However, challenges like fragmented healthcare systems and data privacy concerns remain. Latin America and the Middle East & Africa represent smaller segments, currently at around 5% and 3% respectively. These regions face hurdles like limited technological infrastructure and a shortage of skilled professionals, but hold potential for future growth with increasing healthcare investments and growing awareness of AI's potential.
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REGIONAL COVERAGE:
North America
US
Canada
Mexico
Europe
Eastern Europe
Poland
Romania
Hungary
Turkey
Rest of Eastern Europe
Western Europe
Germany
France
UK
Italy
Spain
Netherlands
Switzerland
Austria
Rest of Western Europe
Asia Pacific
China
India
Japan
South Korea
Vietnam
Singapore
Australia
Rest of Asia Pacific
Middle East & Africa
Middle East
UAE
Egypt
Saudi Arabia
Qatar
Rest of the Middle East
Africa
Nigeria
South Africa
Rest of Africa
Latin America
Brazil
Argentina
Colombia
Rest of Latin America
The Major Players are AliveCor Inc., Digital Diagnostics, Inc., Zebra Medical Vision, Inc., Imagen Technologies, Vuno, Inc., Neural Analytics, Aidence B.V., Siemens Healthineers , GE Healthcare, Riverain Technologies, Aidoc and other players.
Siemens Healthineers: Their Thoracic Care Suite continued to be a leader in using AI for chest anomaly detection.
Zebra Medical Vision: Partnered with Storm ID to develop AI algorithms for diagnosing osteoporosis using a combination of medical images and electronic health information.
AliveCor: Received US FDA approval for their Kardia AI V2 for advanced ECG diagnostics.
| Report Attributes | Details |
|---|---|
| Market Size in 2024 | US$ 1172.6 million |
| Market Size by 2031 | US$ 6341.68 million |
| CAGR | CAGR of 23.49% From 2024 to 2031 |
| Base Year | 2023 |
| Forecast Period | 2024-2031 |
| Historical Data | 2020-2022 |
| Report Scope & Coverage | Market Size, Segments Analysis, Competitive Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook |
| Key Segments |
|
| Regional Analysis/Coverage | North America (US, Canada, Mexico), Europe (Eastern Europe [Poland, Romania, Hungary, Turkey, Rest of Eastern Europe] Western Europe] Germany, France, UK, Italy, Spain, Netherlands, Switzerland, Austria, Rest of Western Europe]), Asia Pacific (China, India, Japan, South Korea, Vietnam, Singapore, Australia, Rest of Asia Pacific), Middle East & Africa (Middle East [UAE, Egypt, Saudi Arabia, Qatar, Rest of Middle East], Africa [Nigeria, South Africa, Rest of Africa], Latin America (Brazil, Argentina, Colombia, Rest of Latin America) |
| Company Profiles | AliveCor Inc., Digital Diagnostics, Inc., Zebra Medical Vision, Inc., Imagen Technologies, Vuno, Inc., Neural Analytics, Aidence B.V., Siemens Healthineers , GE Healthcare, Riverain Technologies., Aidoc |
Ans: The Artificial Intelligence (AI) In Diagnostics Market Size was valued at US$ 1172.6 mn in 2023.
Ans. Top-down, bottom-up, Quantitative, Qualitative Research, Descriptive, Analytical, Applied, Fundamental Research.
Ans. Rising Economic Burden on Medical Facilities and Requirement of High Initial Investment these are major challenges faced by them.
Ans. AliveCor Inc., Digital Diagnostics, Inc., Zebra Medical Vision, Inc., Imagen Technologies, Vuno, Inc., Neural Analytics, Aidence B.V., Siemens Healthineers , GE Healthcare, Riverain Technologies, Digital Diagnostics Inc., Aidoc are top key players of this market.
Ans. Market is expected to growing at a 23.49% CAGR over the forecasted period of 2024 to 2031.
Table of Contents
1. Introduction
1.1 Market Definition
1.2 Scope
1.3 Research Assumptions
2. Industry Flowchart
3. Research Methodology
4. Market Dynamics
4.1 Drivers
4.2 Restraints
4.3 Opportunities
4.4 Challenges
5. Impact Analysis
5.1 Impact Of Russia Ukraine Crisis
5.2 Impact of Economic Slowdown on Major Countries
5.2.1 Introduction
5.2.2 United States
5.2.3 Canada
5.2.4 Germany
5.2.5 France
5.2.6 UK
5.2.7 China
5.2.8 Japan
5.2.9 South Korea
5.2.10 India
6. Value Chain Analysis
7. Porter’s 5 Forces Model
8. Pest Analysis
9. Artificial Intelligence in Diagnostics Market Segmentation, By Component
9.1 Introduction
9.2 Trend Analysis
9.3 Software
9.4 Hardware
9.5 Services
10. Artificial Intelligence in Diagnostics Market Segmentation, By Diagnosis Type
10.1 Introduction
10.2 Trend Analysis
10.3 Cardiology
10.4 Oncology
10.5 Pathology
10.6 Radiology
10.7 Chest and Lung
10.8 Neurology
10.9 Others
11. Regional Analysis
11.1 Introduction
11.2 North America
11.2.1 Trend Analysis
11.2.2 North America Artificial Intelligence in Diagnostics Market by Country
11.2.3 North America Artificial Intelligence in Diagnostics Market By Component
11.2.4 North America Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.2.5 USA
11.2.5.1 USA Artificial Intelligence in Diagnostics Market By Component
11.2.5.2 USA Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.2.6 Canada
11.2.6.1 Canada Artificial Intelligence in Diagnostics Market By Component
11.2.6.2 Canada Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.2.7 Mexico
11.2.7.1 Mexico Artificial Intelligence in Diagnostics Market By Component
11.2.7.2 Mexico Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.3 Europe
11.3.1 Trend Analysis
11.3.2 Eastern Europe
11.3.2.1 Eastern Europe Artificial Intelligence in Diagnostics Market by Country
11.3.2.2 Eastern Europe Artificial Intelligence in Diagnostics Market By Component
11.3.2.3 Eastern Europe Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.3.2.4 Poland
11.3.2.4.1 Poland Artificial Intelligence in Diagnostics Market By Component
11.3.2.4.2 Poland Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.3.2.5 Romania
11.3.2.5.1 Romania Artificial Intelligence in Diagnostics Market By Component
11.3.2.5.2 Romania Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.3.2.6 Hungary
11.3.2.6.1 Hungary Artificial Intelligence in Diagnostics Market By Component
11.3.2.6.2 Hungary Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.3.2.7 Turkey
11.3.2.7.1 Turkey Artificial Intelligence in Diagnostics Market By Component
11.3.2.7.2 Turkey Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.3.2.8 Rest of Eastern Europe
11.3.2.8.1 Rest of Eastern Europe Artificial Intelligence in Diagnostics Market By Component
11.3.2.8.2 Rest of Eastern Europe Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.3.3 Western Europe
11.3.3.1 Western Europe Artificial Intelligence in Diagnostics Market by Country
11.3.3.2 Western Europe Artificial Intelligence in Diagnostics Market By Component
11.3.3.3 Western Europe Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.3.3.4 Germany
11.3.3.4.1 Germany Artificial Intelligence in Diagnostics Market By Component
11.3.3.4.2 Germany Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.3.3.5 France
11.3.3.5.1 France Artificial Intelligence in Diagnostics Market By Component
11.3.3.5.2 France Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.3.3.6 UK
11.3.3.6.1 UK Artificial Intelligence in Diagnostics Market By Component
11.3.3.6.2 UK Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.3.3.7 Italy
11.3.3.7.1 Italy Artificial Intelligence in Diagnostics Market By Component
11.3.3.7.2 Italy Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.3.3.8 Spain
11.3.3.8.1 Spain Artificial Intelligence in Diagnostics Market By Component
11.3.3.8.2 Spain Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.3.3.9 Netherlands
11.3.3.9.1 Netherlands Artificial Intelligence in Diagnostics Market By Component
11.3.3.9.2 Netherlands Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.3.3.10 Switzerland
11.3.3.10.1 Switzerland Artificial Intelligence in Diagnostics Market By Component
11.3.3.10.2 Switzerland Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.3.3.11 Austria
11.3.3.11.1 Austria Artificial Intelligence in Diagnostics Market By Component
11.3.3.11.2 Austria Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.3.3.12 Rest of Western Europe
11.3.3.12.1 Rest of Western Europe Artificial Intelligence in Diagnostics Market By Component
11.3.2.12.2 Rest of Western Europe Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.4 Asia-Pacific
11.4.1 Trend Analysis
11.4.2 Asia Pacific Artificial Intelligence in Diagnostics Market by Country
11.4.3 Asia Pacific Artificial Intelligence in Diagnostics Market By Component
11.4.4 Asia Pacific Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.4.5 China
11.4.5.1 China Artificial Intelligence in Diagnostics Market By Component
11.4.5.2 China Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.4.6 India
11.4.6.1 India Artificial Intelligence in Diagnostics Market By Component
11.4.6.2 India Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.4.7 Japan
11.4.7.1 Japan Artificial Intelligence in Diagnostics Market By Component
11.4.7.2 Japan Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.4.8 South Korea
11.4.8.1 South Korea Artificial Intelligence in Diagnostics Market By Component
11.4.8.2 South Korea Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.4.9 Vietnam
11.4.9.1 Vietnam Artificial Intelligence in Diagnostics Market By Component
11.4.9.2 Vietnam Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.4.10 Singapore
11.4.10.1 Singapore Artificial Intelligence in Diagnostics Market By Component
11.4.10.2 Singapore Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.4.11 Australia
11.4.11.1 Australia Artificial Intelligence in Diagnostics Market By Component
11.4.11.2 Australia Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.4.12 Rest of Asia-Pacific
11.4.12.1 Rest of Asia-Pacific Artificial Intelligence in Diagnostics Market By Component
11.4.12.2 Rest of Asia-Pacific Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.5 Middle East & Africa
11.5.1 Trend Analysis
11.5.2 Middle East
11.5.2.1 Middle East Artificial Intelligence in Diagnostics Market by Country
11.5.2.2 Middle East Artificial Intelligence in Diagnostics Market By Component
11.5.2.3 Middle East Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.5.2.4 UAE
11.5.2.4.1 UAE Artificial Intelligence in Diagnostics Market By Component
11.5.2.4.2 UAE Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.5.2.5 Egypt
11.5.2.5.1 Egypt Artificial Intelligence in Diagnostics Market By Component
11.5.2.5.2 Egypt Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.5.2.6 Saudi Arabia
11.5.2.6.1 Saudi Arabia Artificial Intelligence in Diagnostics Market By Component
11.5.2.6.2 Saudi Arabia Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.5.2.7 Qatar
11.5.2.7.1 Qatar Artificial Intelligence in Diagnostics Market By Component
11.5.2.7.2 Qatar Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.5.2.8 Rest of Middle East
11.5.2.8.1 Rest of Middle East Artificial Intelligence in Diagnostics Market By Component
11.5.2.8.2 Rest of Middle East Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.5.3 Africa
11.5.3.1 Africa Artificial Intelligence in Diagnostics Market by Country
11.5.3.2 Africa Artificial Intelligence in Diagnostics Market By Component
11.5.3.3 Africa Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.5.2.4 Nigeria
11.5.2.4.1 Nigeria Artificial Intelligence in Diagnostics Market By Component
11.5.2.4.2 Nigeria Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.5.2.5 South Africa
11.5.2.5.1 South Africa Artificial Intelligence in Diagnostics Market By Component
11.5.2.5.2 South Africa Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.5.2.6 Rest of Africa
11.5.2.6.1 Rest of Africa Artificial Intelligence in Diagnostics Market By Component
11.5.2.6.2 Rest of Africa Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.6 Latin America
11.6.1 Trend Analysis
11.6.2 Latin America Artificial Intelligence in Diagnostics Market by Country
11.6.3 Latin America Artificial Intelligence in Diagnostics Market By Component
11.6.4 Latin America Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.6.5 Brazil
11.6.5.1 Brazil Artificial Intelligence in Diagnostics Market By Component
11.6.5.2 Brazil Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.6.6 Argentina
11.6.6.1 Argentina Artificial Intelligence in Diagnostics Market By Component
11.6.6.2 Argentina Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.6.7 Colombia
11.6.7.1 Colombia Artificial Intelligence in Diagnostics Market By Component
11.6.7.2 Colombia Artificial Intelligence in Diagnostics Market By Diagnosis Type
11.6.8 Rest of Latin America
11.6.8.1 Rest of Latin America Artificial Intelligence in Diagnostics Market By Component
11.6.8.2 Rest of Latin America Artificial Intelligence in Diagnostics Market By Diagnosis Type
12. Company Profiles
12.1 AliveCor Inc.
12.1.1 Company Overview
12.1.2 Financial
12.1.3 Products/ Services Offered
12.1.4 SWOT Analysis
12.1.5 The SNS View
12.2 Digital Diagnostics, Inc.
12.2.1 Company Overview
12.2.2 Financial
12.2.3 Products/ Services Offered
12.2.4 SWOT Analysis
12.2.5 The SNS View
12.3 Zebra Medical Vision, Inc.
12.3.1 Company Overview
12.3.2 Financial
12.3.3 Products/ Services Offered
12.3.4 SWOT Analysis
12.3.5 The SNS View
12.4 Imagen Technologies
12.4.1 Company Overview
12.4.2 Financial
12.4.3 Products/ Services Offered
12.4.4 SWOT Analysis
12.4.5 The SNS View
12.5 Vuno, Inc.
12.5.1 Company Overview
12.5.2 Financial
12.5.3 Products/ Services Offered
12.5.4 SWOT Analysis
12.5.5 The SNS View
12.6 Neural Analytics
12.6.1 Company Overview
12.6.2 Financial
12.6.3 Products/ Services Offered
12.6.4 SWOT Analysis
12.6.5 The SNS View
12.7 Aidence B.V.
12.7.1 Company Overview
12.7.2 Financial
12.7.3 Products/ Services Offered
12.7.4 SWOT Analysis
12.7.5 The SNS View
12.8 Siemens Healthineers
12.8.1 Company Overview
12.8.2 Financial
12.8.3 Products/ Services Offered
12.8.4 SWOT Analysis
12.8.5 The SNS View
12.9 GE Healthcare
12.9.1 Company Overview
12.9.2 Financial
12.9.3 Products/ Services Offered
12.9.4 SWOT Analysis
12.9.5 The SNS View
12.10 Riverain Technologies
12.10.1 Company Overview
12.10.2 Financial
12.10.3 Products/ Services Offered
12.10.4 SWOT Analysis
12.10.5 The SNS View
12.11 Aidoc
12.11.1 Company Overview
12.11.2 Financial
12.11.3 Products/ Services Offered
12.11.4 SWOT Analysis
12.11.5 The SNS View
13. Competitive Landscape
13.1 Competitive Benchmarking
13.2 Market Share Analysis
13.3 Recent Developments
13.3.1 Industry News
13.3.2 Company News
13.3.3 Mergers & Acquisitions
14. USE Cases And Best Practices
15. Conclusion
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