Artificial Intelligence (AI) in Diagnostics Market Size was valued at USD 1.25 Billion in 2023 and is expected to reach USD 7.75 Billion by 2032, growing at a CAGR of 22.5% over the forecast period 2024-2032.
The Artificial Intelligence (AI) in Diagnostics Market report, provides statistical insights & trends of AI-assisted diagnosis prevalence, adoption in hospitals & clinics, and AI-powered imaging & pathology analysis. The report provides details analysis of healthcare spending on AI diagnostics, with investment breakdowns by governments, insurers, and private providers AI has an impact on workflow and cost. Report also follows regulatory approvals (FDA, EMA, etc.) and compliance trends, alongside AI workflow, efficiency and cost savings data related to reduced diagnosis time & errors, and operational cost reduction via AI. The Artificial Intelligence (AI) in Diagnostics market is experiencing robust growth, driven by the increasing prevalence of chronic diseases and advancements in AI technologies.
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Market Dynamics:
Drivers
Rapid advancements in AI technology enhance diagnostic accuracy and efficiency.
Artificial intelligence (AI) is developing rapidly, which is improving the quality and efficiency of diagnosis in healthcare. One key recent example is the NHS's announcement of the world's largest breast cancer diagnosis AI trial, with around 700,000 mammograms. The trial will evaluate whether AI it better than radiologists in identifying breast cancer, which could help facilitate diagnosis and help maximize use of specialists.
AI tools have proven better than traditional methods in the detection of prostate cancer. According to a UCLA study, an AI was able to identify prostate cancer with an 84% accuracy rate while human doctors performed at 67% accuracy. From clinical data, the ASIST AI used a doctors' algorithm to produce 3D maps estimating where the cancer was, helping identify precise cancer margins. In addition, AI is advancing the early detection of diseases such as Alzheimer's. An AI tool that can predict the onset of Alzheimer's disease 80% accurately has been developed by researchers at Cambridge University. This algorithm analyzes cognitive test results and MRI scans, offering predictions that are three times more accurate than current clinical methods. Notably, these advancements highlight the transformative role of AI in diagnostics and its potential impact in terms of earlier and more precise diagnoses as well as better patient outcomes.
Restraint:
Regulatory uncertainties and the need for robust validation of AI diagnostic tools.
The integration of AI in diagnostics faces significant challenges with regulatory uncertainties. A recent review by the Innovation Ecosystem Programme, commissioned by NHS England, highlighted that disjointed policies and a risk-averse culture are hindering health innovation in the UK, potentially preventing patients from benefiting from new technologies. Even as pilot programs have succeeded in reducing the time to diagnosis using AI in radiology by 30%, these barriers are hampering broader advancement. Moreover, nearly 900 AI/ML-based medical devices based on FDA approval or clearance have emerged, with 76% for use in radiology. Continually updating the algorithm regulatory framework is still under development by agencies and adds uncertainty for developers. These examples highlight both the challenges and the evolving nature of AI diagnostic regulatory landscapes.
Opportunity:
Integration of AI with imaging devices for real-time analysis.
Integrating artificial intelligence (AI) with imaging devices offers significant opportunities to enhance diagnostic accuracy and efficiency. As an example, the UK's National Health Service (NHS) has launched the largest breast cancer diagnosis trial with AI in the world using about 700,000 mammograms. The goal of this trial is to compare the performance of AI with that of radiologists at identifying breast cancer to help provide quicker diagnoses and reduce the burden on specialists. In South Australia, the Medical Imaging (SAMI) sites have implemented AI from Annalise.ai Use for chest X-ray diagnoses By using this technology as a sort of "spell check" for X-rays, AI highlights areas of interest and offers potential diagnoses for review to physicians, improving accuracy. Moreover, an AI algorithm has been created that provides 98% high accuracy in detecting diseases from tongue colours. This technique allows to detection of diabetes, cancer, or strokes, making it a non-invasive diagnostic tool. These advancements highlight the disruptive role AI can play in medical imaging for better patient outcomes with early and accurate disease detection.
Challenge
Ensuring data privacy and security in AI-driven diagnostics.
One of the biggest challenges in AI-powered diagnostics is ensuring data privacy and security. One of the leading causes for concern is the vulnerability of data breaches and hacking practices, primarily as such entities are a main target for hackers to expose protected information. Unauthorized access to patient records can lead to identity theft and financial loss. Another challenge is collecting sensitive data without proper consent. If not appropriately handled, the need for huge data can lead to the violation of patient privacy rights in one way or another which is one of the main reasons why patients are not accepting healthcare AI wholeheartedly.
Moreover, data anonymization cannot be regarded as completely safe, and, with studies showing even anonymized datasets to be at risk of re-identification, the implications for patient confidentiality are significant. On top of that, compliance with regulations is another complication. Regulatory compliances like GDPR and HIPAA mandate a considerable amount of resources and policymakers to refine how AI systems operate and ensure compliance with changing national and international legal frameworks. These problems are reflected in public concerns in 2024, nearly half of U.S. adults reported being worried about data privacy and security regarding healthcare AI use. To overcome these challenges, strong encryption, controlled access, and constant assessments of patient data safety are necessary.
By Component
In 2023, 45% of the market revenue share was held by the software component segment as the solutions are crucial for analyzing massive datasets which include electronic health records, and medical imaging. The challenge of shortage of radiologists and rising healthcare expenditure, has compelled many governments out there to actively promote the usage of digital healthcare platforms. Such as, in China, government initiatives are being rolled out for AI-underpinned startups aimed at diagnostic solutions, and in Europe, investment is going toward cross-sector synergies around enablers of AI adoption. Funding initiatives from governments across regions are supporting the adoption of software solutions. North America is another region where heavy investments have been made in the healthcare sector with the U.S. government funding the development of advanced diagnostic software.
AI-based software not only improves diagnostic precision but also reduces workloads for medical professionals. This segment has grown further in strength owing to the increasing focus on big data analytics and machine learning algorithms. Continued demand for software capable of driving efficiency and reducing costs as healthcare systems transition to value-based care models will drive growth in this segment.
By Diagnosis Type
The neurology diagnosis segment accounted for the largest market share in 2023, at 25% of revenues owing to the usage of AI tools for the detection of neurological disorders such as Alzheimer, and Parkinsons disease. Focused governments are identifying research on AI applications in neurology, with large amounts of funding designated to early detection programs. In contrast, radiology is anticipated to see the highest growth rate during the forecast period owing to developments in hybrid imaging modalities such as PET/MRI15.
The application of machine learning, an important subset of AI, has many key advantages in radiology, including the ability to manipulate large amounts of complex imaging data with significant accuracy. For instance, PET/MRI systems have achieved 87.3% accuracy in detecting cancer, outperforming MRI or PET standalone modalities. Combined with the government's push towards innovation, this advancement makes for a strong growth profile in radiology.
The AI diagnostics market was dominated by North America in 2023 with a revenue share of 57%. The region enjoys such dominance because of a mature healthcare infrastructure, a significant adoption rate of AI-enabled technologies, and robust financial backing from both the public and private fronts. The US was the primary contributor to this leadership, accounting for USD 412.2 million in revenue, driven mainly by the government, big investments, and a strong relationship between healthcare vendors and AI solution vendors. Moreover, the growing utilization of AI for initial disease identification, customized treatment plans, and process optimization in medical diagnostics has also bolstered the North American market.
Asia Pacific is anticipated to witness the highest CAGR over the forecast period, emerging as the key growth engine for AI diagnostics. This rapid acceptance of AI-founded medical analysis is due to the expanded electronic healthcare world and effective government initiatives in countries like China, India, and Japan. Countries such as these are also creating a regulatory environment that will see them invest heavily into AI-driven health solutions whilst creating a public institution and technology providers alliance. Nonprofit organizations and international funding agencies are also promoting AI-powered health accessibility and affordability initiatives as well. The use of AI diagnostics is critical in tackling growing healthcare demand; insufficient physician supply and cost-efficiency challenges in the region.
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Key Service Providers/Manufacturers
IBM Watson Health (Watson for Oncology, Imaging AI)
GE Healthcare (Edison AI, Critical Care Suite)
Siemens Healthineers (AI-Rad Companion, syngo.via)
Philips Healthcare (IntelliSpace AI Workflow Suite, AI Manager)
Aidoc (Aidoc Radiology AI, Aidoc Cardiology AI)
Qure.ai (qXR, qER)
Zebra Medical Vision (HealthCXR, HealthMammo)
Arterys (Arterys Cardio AI, Arterys Lung AI)
Lunit (Lunit INSIGHT CXR, Lunit INSIGHT MMG)
DeepMind (Google Health) (Streams AI, AlphaFold AI)
Key Users
Mayo Clinic
Cleveland Clinic
Johns Hopkins Medicine
Massachusetts General Hospital
Stanford Health Care
Mount Sinai Health System
Apollo Hospitals
National Institutes of Health (NIH)
Harvard Medical School
University College London Hospitals (UCLH)
GE HealthCare launched Revolution RT, a CT solution that aims to enhance both precision and workflow in radiation therapy on May 1, 2024. The company also announced innovations in iRT features at ESTRO 2024, along with recently-acquired MIM Software.
QAi Prostate, an advanced diagnostic tool for prostate cancer, was launched by Qritive in March 2023. This includes an artificial intelligence algorithm that assists pathologists in the identification of prostatic adenocarcinoma and differentiation of malignant from benign tumors in biopsy material.
| Report Attributes | Details |
|---|---|
|
Market Size in 2023 |
USD 1.25 Billion |
|
Market Size by 2032 |
USD 7.75 Billion |
|
CAGR |
CAGR of 22.5% From 2024 to 2032 |
|
Base Year |
2023 |
|
Forecast Period |
2024-2032 |
|
Historical Data |
2020-2022 |
|
Report Scope & Coverage |
Market Size, Segments Analysis, Competitive Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook |
|
Key Segments |
• By Component (Software, Hardware, Services) |
|
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 |
Philips Healthcare, Cerner Corporation, Allscripts Healthcare Solutions, Epic Systems Corporation, IBM Watson Health, Salesforce Health Cloud, Optum (UnitedHealth Group), Medecision, eClinicalWorks, Health Catalyst |
Ans. The projected market size for the Artificial Intelligence (AI) in Diagnostics Market is USD 7.75 Billion by 2032.
Ans: The North American region dominated the Artificial Intelligence (AI) in Diagnostics Market in 2023.
Ans. The CAGR of the Artificial Intelligence (AI) in Diagnostics Market is 22.5% During the forecast period of 2024-2032.
Ans: The major key players in the market are IBM Watson Health, GE Healthcare, Siemens Healthineers, Philips Healthcare, Aidoc, Qure.ai, Zebra Medical Vision, Arterys, Lunit, DeepMind (Google Health), and others in the final report.
Ans: The Software segment dominated the Artificial Intelligence (AI) in Diagnostics Market.
1. Introduction
1.1 Market Definition
1.2 Scope (Inclusion and Exclusions)
1.3 Research Assumptions
2. Executive Summary
2.1 Market Overview
2.2 Regional Synopsis
2.3 Competitive Summary
3. Research Methodology
3.1 Top-Down Approach
3.2 Bottom-up Approach
3.3. Data Validation
3.4 Primary Interviews
4. Market Dynamics Impact Analysis
4.1 Market Driving Factors Analysis
4.1.2 Drivers
4.1.2 Restraints
4.1.3 Opportunities
4.1.4 Challenges
4.2 PESTLE Analysis
4.3 Porter’s Five Forces Model
5. Statistical Insights and Trends Reporting
5.1 Incidence and Prevalence of AI-Assisted Diagnoses (2023)
5.2 Adoption Rates of AI in Diagnostics (2023)
5.3 Healthcare Spending on AI in Diagnostics (2023)
5.4 Regulatory Approvals and Compliance Trends (2023)
6. Competitive Landscape
6.1 List of Major Companies, By Region
6.2 Market Share Analysis, By Region
6.3 Product Benchmarking
6.3.1 Product specifications and features
6.3.2 Pricing
6.4 Strategic Initiatives
6.4.1 Marketing and promotional activities
6.4.2 Distribution and supply chain strategies
6.4.3 Expansion plans and new product launches
6.4.4 Strategic partnerships and collaborations
6.5 Technological Advancements
6.6 Market Positioning and Branding
7. Artificial Intelligence (AI) in Diagnostics Market Segmentation, By Component
7.1 Chapter Overview
7.2 Software
7.2.1 Software Market Trends Analysis (2020-2032)
7.2.2 Software Market Size Estimates and Forecasts to 2032 (USD Billion)
7.3 Hardware
7.3.1 Hardware Market Trends Analysis (2020-2032)
7.3.2 Hardware Market Size Estimates and Forecasts to 2032 (USD Billion)
7.4 Services
7.4.1 Services Market Trends Analysis (2020-2032)
7.4.2 Services Market Size Estimates and Forecasts to 2032 (USD Billion)
8. Artificial Intelligence (AI) in Diagnostics Market Segmentation, By Diagnosis Type
8.1 Chapter Overview
8.2 Cardiology
8.2.1 Cardiology Market Trends Analysis (2020-2032)
8.2.2 Cardiology Market Size Estimates and Forecasts to 2032 (USD Billion)
8.3 Radiology
8.3.1 Radiology Market Trends Analysis (2020-2032)
8.3.2 Radiology Market Size Estimates and Forecasts to 2032 (USD Billion)
8.4 Oncology
8.4.1 Oncology Market Trends Analysis (2020-2032)
8.4.2 Oncology Market Size Estimates and Forecasts to 2032 (USD Billion)
8.5 Pathology
8.5.1 Pathology Market Trends Analysis (2020-2032)
8.5.2 Pathology Market Size Estimates and Forecasts to 2032 (USD Billion)
8.6 Chest and Lung
8.6.1 Chest and Lung Market Trends Analysis (2020-2032)
8.6.2 Chest and Lung Market Size Estimates and Forecasts to 2032 (USD Billion)
8.7 Neurology
8.7.1 Neurology Market Trends Analysis (2020-2032)
8.7.2 Neurology Market Size Estimates and Forecasts to 2032 (USD Billion)
8.8 Others
8.8.1 Others Market Trends Analysis (2020-2032)
8.8.2 Others Market Size Estimates and Forecasts to 2032 (USD Billion)
9. Regional Analysis
9.1 Chapter Overview
9.2 North America
9.2.1 Trends Analysis
9.2.2 North America Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, by Country (2020-2032) (USD Billion)
9.2.3 North America Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.2.4 North America Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.2.5 USA
9.2.5.1 USA Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.2.5.2 USA Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.2.6 Canada
9.2.6.1 Canada Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.2.6.2 Canada Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.2.7 Mexico
9.2.7.1 Mexico Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.2.7.2 Mexico Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.3 Europe
9.3.1 Eastern Europe
9.3.1.1 Trends Analysis
9.3.1.2 Eastern Europe Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, by Country (2020-2032) (USD Billion)
9.3.1.3 Eastern Europe Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.3.1.4 Eastern Europe Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.3.1.5 Poland
9.3.1.5.1 Poland Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.3.1.5.2 Poland Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.3.1.6 Romania
9.3.1.6.1 Romania Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.3.1.6.2 Romania Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.3.1.7 Hungary
9.3.1.7.1 Hungary Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.3.1.7.2 Hungary Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.3.1.8 Turkey
9.3.1.8.1 Turkey Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.3.1.8.2 Turkey Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.3.1.9 Rest of Eastern Europe
9.3.1.9.1 Rest of Eastern Europe Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.3.1.9.2 Rest of Eastern Europe Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.3.2 Western Europe
9.3.2.1 Trends Analysis
9.3.2.2 Western Europe Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, by Country (2020-2032) (USD Billion)
9.3.2.3 Western Europe Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.3.2.4 Western Europe Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.3.2.5 Germany
9.3.2.5.1 Germany Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.3.2.5.2 Germany Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.3.2.6 France
9.3.2.6.1 France Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.3.2.6.2 France Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.3.2.7 UK
9.3.2.7.1 UK Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.3.2.7.2 UK Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.3.2.8 Italy
9.3.2.8.1 Italy Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.3.2.8.2 Italy Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.3.2.9 Spain
9.3.2.9.1 Spain Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.3.2.9.2 Spain Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.3.2.10 Netherlands
9.3.2.10.1 Netherlands Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.3.2.10.2 Netherlands Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.3.2.11 Switzerland
9.3.2.11.1 Switzerland Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.3.2.11.2 Switzerland Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.3.2.12 Austria
9.3.2.12.1 Austria Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.3.2.12.2 Austria Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.3.2.13 Rest of Western Europe
9.3.2.13.1 Rest of Western Europe Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.3.2.13.2 Rest of Western Europe Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.4 Asia Pacific
9.4.1 Trends Analysis
9.4.2 Asia Pacific Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, by Country (2020-2032) (USD Billion)
9.4.3 Asia Pacific Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.4.4 Asia Pacific Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.4.5 China
9.4.5.1 China Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.4.5.2 China Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.4.6 India
9.4.5.1 India Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.4.5.2 India Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.4.5 Japan
9.4.5.1 Japan Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.4.5.2 Japan Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.4.6 South Korea
9.4.6.1 South Korea Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.4.6.2 South Korea Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.4.7 Vietnam
9.4.7.1 Vietnam Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.2.7.2 Vietnam Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.4.8 Singapore
9.4.8.1 Singapore Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.4.8.2 Singapore Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.4.9 Australia
9.4.9.1 Australia Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.4.9.2 Australia Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.4.10 Rest of Asia Pacific
9.4.10.1 Rest of Asia Pacific Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.4.10.2 Rest of Asia Pacific Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.5 Middle East and Africa
9.5.1 Middle East
9.5.1.1 Trends Analysis
9.5.1.2 Middle East Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, by Country (2020-2032) (USD Billion)
9.5.1.3 Middle East Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.5.1.4 Middle East Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.5.1.5 UAE
9.5.1.5.1 UAE Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.5.1.5.2 UAE Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.5.1.6 Egypt
9.5.1.6.1 Egypt Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.5.1.6.2 Egypt Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.5.1.7 Saudi Arabia
9.5.1.7.1 Saudi Arabia Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.5.1.7.2 Saudi Arabia Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.5.1.8 Qatar
9.5.1.8.1 Qatar Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.5.1.8.2 Qatar Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.5.1.9 Rest of Middle East
9.5.1.9.1 Rest of Middle East Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.5.1.9.2 Rest of Middle East Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.5.2 Africa
9.5.2.1 Trends Analysis
9.5.2.2 Africa Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, by Country (2020-2032) (USD Billion)
9.5.2.3 Africa Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.5.2.4 Africa Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.5.2.5 South Africa
9.5.2.5.1 South Africa Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.5.2.5.2 South Africa Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.5.2.6 Nigeria
9.5.2.6.1 Nigeria Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.5.2.6.2 Nigeria Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.5.2.7 Rest of Africa
9.5.2.7.1 Rest of Africa Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.5.2.7.2 Rest of Africa Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.6 Latin America
9.6.1 Trends Analysis
9.6.2 Latin America Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, by Country (2020-2032) (USD Billion)
9.6.3 Latin America Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.6.4 Latin America Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.6.5 Brazil
9.6.5.1 Brazil Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.6.5.2 Brazil Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.6.6 Argentina
9.6.6.1 Argentina Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.6.6.2 Argentina Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.6.7 Colombia
9.6.7.1 Colombia Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.6.7.2 Colombia Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
9.6.8 Rest of Latin America
9.6.8.1 Rest of Latin America Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Component (2020-2032) (USD Billion)
9.6.8.2 Rest of Latin America Artificial Intelligence (AI) in Diagnostics Market Estimates and Forecasts, By Diagnosis Type (2020-2032) (USD Billion)
10. Company Profiles
10.1 IBM Watson Health
10.1.1 Company Overview
10.1.2 Financial
10.1.3 Products/ Services Offered
110.1.4 SWOT Analysis
10.2 GE Healthcare
10.2.1 Company Overview
10.2.2 Financial
10.2.3 Products/ Services Offered
10.2.4 SWOT Analysis
10.3 Siemens Healthineers
10.3.1 Company Overview
10.3.2 Financial
10.3.3 Products/ Services Offered
10.3.4 SWOT Analysis
10.4 Philips Healthcare
10.4.1 Company Overview
10.4.2 Financial
10.4.3 Products/ Services Offered
10.4.4 SWOT Analysis
10.5 Aidoc
10.5.1 Company Overview
10.5.2 Financial
10.5.3 Products/ Services Offered
10.5.4 SWOT Analysis
10.6 Qure.ai
10.6.1 Company Overview
10.6.2 Financial
10.6.3 Products/ Services Offered
10.6.4 SWOT Analysis
10.7 Zebra Medical Vision
10.7.1 Company Overview
10.7.2 Financial
10.7.3 Products/ Services Offered
10.7.4 SWOT Analysis
10.8 Arterys
10.8.1 Company Overview
10.8.2 Financial
10.8.3 Products/ Services Offered
10.8.4 SWOT Analysis
10.9 Lunit
10.9.1 Company Overview
10.9.2 Financial
10.9.3 Products/ Services Offered
10.9.4 SWOT Analysis
10.10 DeepMind (Google Health)
10.9.1 Company Overview
10.9.2 Financial
10.9.3 Products/ Services Offered
10.9.4 SWOT Analysis
11. Use Cases and Best Practices
12. Conclusion
An accurate research report requires proper strategizing as well as implementation. There are multiple factors involved in the completion of good and accurate research report and selecting the best methodology to compete the research is the toughest part. Since the research reports we provide play a crucial role in any company’s decision-making process, therefore we at SNS Insider always believe that we should choose the best method which gives us results closer to reality. This allows us to reach at a stage wherein we can provide our clients best and accurate investment to output ratio.
Each report that we prepare takes a timeframe of 350-400 business hours for production. Starting from the selection of titles through a couple of in-depth brain storming session to the final QC process before uploading our titles on our website we dedicate around 350 working hours. The titles are selected based on their current market cap and the foreseen CAGR and growth.
The 5 steps process:
Step 1: Secondary Research:
Secondary Research or Desk Research is as the name suggests is a research process wherein, we collect data through the readily available information. In this process we use various paid and unpaid databases which our team has access to and gather data through the same. This includes examining of listed companies’ annual reports, Journals, SEC filling etc. Apart from this our team has access to various associations across the globe across different industries. Lastly, we have exchange relationships with various university as well as individual libraries.
Step 2: Primary Research
When we talk about primary research, it is a type of study in which the researchers collect relevant data samples directly, rather than relying on previously collected data. This type of research is focused on gaining content specific facts that can be sued to solve specific problems. Since the collected data is fresh and first hand therefore it makes the study more accurate and genuine.
We at SNS Insider have divided Primary Research into 2 parts.
Part 1 wherein we interview the KOLs of major players as well as the upcoming ones across various geographic regions. This allows us to have their view over the market scenario and acts as an important tool to come closer to the accurate market numbers. As many as 45 paid and unpaid primary interviews are taken from both the demand and supply side of the industry to make sure we land at an accurate judgement and analysis of the market.
This step involves the triangulation of data wherein our team analyses the interview transcripts, online survey responses and observation of on filed participants. The below mentioned chart should give a better understanding of the part 1 of the primary interview.
Part 2: In this part of primary research the data collected via secondary research and the part 1 of the primary research is validated with the interviews from individual consultants and subject matter experts.
Consultants are those set of people who have at least 12 years of experience and expertise within the industry whereas Subject Matter Experts are those with at least 15 years of experience behind their back within the same space. The data with the help of two main processes i.e., FGDs (Focused Group Discussions) and IDs (Individual Discussions). This gives us a 3rd party nonbiased primary view of the market scenario making it a more dependable one while collation of the data pointers.
Step 3: Data Bank Validation
Once all the information is collected via primary and secondary sources, we run that information for data validation. At our intelligence centre our research heads track a lot of information related to the market which includes the quarterly reports, the daily stock prices, and other relevant information. Our data bank server gets updated every fortnight and that is how the information which we collected using our primary and secondary information is revalidated in real time.
Step 4: QA/QC Process
After all the data collection and validation our team does a final level of quality check and quality assurance to get rid of any unwanted or undesired mistakes. This might include but not limited to getting rid of the any typos, duplication of numbers or missing of any important information. The people involved in this process include technical content writers, research heads and graphics people. Once this process is completed the title gets uploader on our platform for our clients to read it.
Step 5: Final QC/QA Process:
This is the last process and comes when the client has ordered the study. In this process a final QA/QC is done before the study is emailed to the client. Since we believe in giving our clients a good experience of our research studies, therefore, to make sure that we do not lack at our end in any way humanly possible we do a final round of quality check and then dispatch the study to the client.
By Component
Software
Hardware
Services
By Diagnosis Type
Cardiology
Radiology
Oncology
Pathology
Chest and Lung
Neurology
Others
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Rest of Eastern Europe
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Rest of Western Europe
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Rest of Asia Pacific
Middle East & Africa
Middle East
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Rest of Middle East
Africa
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Rest of Africa
Latin America
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Rest of Latin America
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Available Customization
With the given market data, SNS Insider offers customization as per the company’s specific needs. The following customization options are available for the report:
Detailed Volume Analysis
Criss-Cross segment analysis (e.g. Product X Application)
Competitive Product Benchmarking
Geographic Analysis
Additional countries in any of the regions
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Detailed analysis and profiling of additional market players
The Surgical Retractors Market Size was valued at USD 2.12 billion in 2023 and is expected to reach USD 3.81 billion by 2032 and grow at a CAGR of 6.74% by 2024-2032.
The Hospital Information System Market Size was valued at USD 56.84 billion in 2023 and is projected to reach USD 100.66 billion by 2032, with a CAGR of 6.58% over the forecast period 2024-2032.
The 5G In Healthcare Market Size was valued at USD 50.64 Bn in 2023 and will reach to USD 834.24 Bn by 2032 and grow at a CAGR of 36.56% by 2024 to 2032.
The Biosimilars Market size was valued at USD 29.51 billion in 2023 and is projected to reach USD 127.92 billion by 2032, growing at a CAGR of 17.7%
The Healthcare Automation Market size was valued at USD 46.54 billion in 2023 and is expected to reach USD 86.71 billion by 2031 and grow at a CAGR of 8.11% over the forecast period of 2024-2031.
The DNA Sequencing Market Size was valued at USD 11.5 Billion in 2023 and is expected to reach USD 52.1 Billion by 2032, growing at a CAGR of 17.8% Over the Forecast Period of 2024-2032.
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