NEW YORK – Nova one advisor recently added a research report, Artificial Intelligence (Ai) In Medical Diagnostics market – global industry size, share analysis, market dynamics, market risk factors, market opportunities and challenges. segment forecast and the geographical distribution of the global market, profitability graph and the regional outlook of this business vertical.
Market Size; The global Artificial Intelligence (Ai) In Medical Diagnostics market size was valued at US$ 608 million in 2020 and is projected to reach US$ 4,978 million by 2027, rising at a market growth (CAGR) of 52.4% during the forecast period.
Growth in this market is primarily driven by government initiatives to increase the adoption of AI-based technologies, increasing demand for AI tools in the medical field, growing focus on reducing the workload of radiologists, influx of large and complex datasets, growth in funding for AI-based start-ups, and the growing number of cross-industry partnerships and collaborations.
NOTE: Our report highlights the major issues and hazards that companies might come across due to the unprecedented outbreak of COVID-19.
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A recent report provides crucial insights along with application based and forecast information in the Global Artificial Intelligence (Ai) In Medical Diagnostics Market. The report provides a comprehensive analysis of key factors that are expected to drive the growth of this market. This study also provides a detailed overview of the opportunities along with the current trends observed in the Artificial Intelligence (Ai) In Medical Diagnostics market.
With increasing cases of obesity all over the globe, a need for conducting an in-depth study about this healthcare issue led to the development of this report. Increasing binge eating and consumption of junk foods, neglect towards regular exercise, rising levels of stress, are key market drivers. The report discusses more information about these subjects, with a focus on the rising need for Artificial Intelligence (Ai) In Medical Diagnostics.
A quantitative analysis of the industry is compiled for a period of 10 years in order to assist players to grow in the market. Insights on specific revenue figures generated are also given in the report, along with projected revenue at the end of the forecast period. With healthcare being a sensitive topic, a separate analysis is included that discusses the widespread continuing obesity all over the globe consequently increasing demand for surgical devices.
Highlights of the Report:
In-depth analysis of various insights, namely, Artificial Intelligence (Ai) In Medical Diagnostics Market trends, growth drivers, opportunities, and other related challenges.
Comprehensive details of key market players, their core competencies, and Artificial Intelligence (Ai) In Medical Diagnostics Market share.
The potency of suppliers and buyers to make better business decisions.
Lists out the market size in terms of volume.
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Companies and Manufacturers Covered
The study covers key players operating in the market along with prime schemes and strategies implemented by each player to hold high positions in the industry. Such a tough vendor landscape provides a competitive outlook of the industry, consequently existing as a key insight. These insights were thoroughly analyzed and prime business strategies and products that offer high revenue generation capacities were indentified. Key players of the global Artificial Intelligence (Ai) In Medical Diagnostics market are included as given below:
List of KEY PLAYERS in Artificial Intelligence (Ai) In Medical Diagnostics Market Report are:
The major market players include: Microsoft Corporation (US), NVIDIA (US), IBM (US), Intel (US), Siemens Healthineers (Germany), GE Healthcare (US), Digital Diagnostics (US), Xilinx (US), InformAI (US), Enlitic (US), Day Zero Diagnostics (US), Aidence (Netherlands), Butterfly Network, Inc. (US), Prognos (US), Zebra Medical Vision (Israel), Viz.ai (US), Quibin (Spain), Qure.ai (India), Therapixel (France), and HeartFlow (US).
Unravelling the Critical Segments
This research report offers market revenue, sales volume, production assessment and prognoses by classifying it on the basis of various aspects including product type, application/end-user, and region. Further, this research study investigates market size, production, consumption and its development trends at global, regional, and country level for period 2017 to 2027 and covers subsequent region in its scope:
By Component
By Application
By End User
Regional Analysis and Forecast
Further, this research study analyses market size, production, consumption and its advancement trends at global, regional, and country level for period 2016 to 2027 and covers following region in its scope:
Important years considered for this report:
Historical Years: 2017-2021
Base Year: 2021
Forecast Period: 2021-2027
Impact of COVID-19 on the Healthcare Industry
The COVID-19 pandemic has caused severe impacts on the global economy at various levels and which can be seen on the Healthcare industry as well. The thriving market of health care research and development is expected to exhibit a steep decline in the sales during the lockdown period owing to the shutdown of the manufacturing units, acute shortage in the supply of raw materials and absence of potential manpower. It can be deduced from the current situations brought about by the pandemic that the production, and supply chain activities have experienced minor hurdles. However, the market is projected to gradually recover post-COVID-19, which will present attractive opportunities for sales across various regions of the world in the following years.
Nova one advisor adopted a multidisciplinary approach during the pandemic-era to focus on the growth and development of the Artificial Intelligence (Ai) In Medical Diagnostics Market. The study features insights on the current growth dynamics and the major revenue reforms prevailing in the market as along with the key takeaways over the forecast.
The team of analysts at Nova one advisor are focussing on research and market study to produce different Artificial Intelligence (Ai) In Medical Diagnostics Market forecasts and predictions at both national and international levels. They have considered several leads of information pertaining to the industry like market figures and merger estimations to assess and produce reliable and informative insights on the Artificial Intelligence (Ai) In Medical Diagnostics Market.
Key Questions Covered in the Report
Reasons to Purchase this Report:
Table of Contents
Chapter 1. Introduction
1.1. Research Objective
1.2. Scope of the Study
1.3. Definition
Chapter 2. Research Methodology
2.1. Research Approach
2.2. Data Sources
2.3. Assumptions & Limitations
Chapter 3. Executive Summary
3.1. Market Snapshot
Chapter 4. Market Variables and Scope
4.1. Introduction
4.2. Market Classification and Scope
4.3. Industry Value Chain Analysis
4.3.1. Raw Material Procurement Analysis
4.3.2. Sales and Distribution Channel Analysis
4.3.3. Downstream Buyer Analysis
Chapter 5. Market Dynamics Analysis and Trends
5.1. Market Dynamics
5.1.1. Market Drivers
5.1.2. Market Restraints
5.1.3. Market Opportunities
5.2. Porter’s Five Forces Analysis
5.2.1. Bargaining power of suppliers
5.2.2. Bargaining power of buyers
5.2.3. Threat of substitute
5.2.4. Threat of new entrants
5.2.5. Degree of competition
Chapter 6. Competitive Landscape
6.1.1. Company Market Share/Positioning Analysis
6.1.2. Key Strategies Adopted by Players
6.1.3. Vendor Landscape
6.1.3.1. List of Suppliers
6.1.3.2. List of Buyers
Chapter 7. Global Artificial Intelligence (Ai) in Medical Diagnostics Market, By Component
7.1. Artificial Intelligence (Ai) in Medical Diagnostics Market, By Component, 2021-2027
7.1.1. Software
7.1.1.1. Market Revenue and Forecast (2016-2027)
7.1.2. Services
7.1.2.1. Market Revenue and Forecast (2016-2027)
Chapter 8. Global Artificial Intelligence (Ai) in Medical Diagnostics Market, By Application
8.1. Artificial Intelligence (Ai) in Medical Diagnostics Market, By Application, 2021-2027
8.1.1. In Vivo Diagnostics
8.1.1.1. Market Revenue and Forecast (2016-2027)
8.1.2. In Vitro Diagnostics
8.1.2.1. Market Revenue and Forecast (2016-2027)
Chapter 9. Global Artificial Intelligence (Ai) in Medical Diagnostics Market, By End User
9.1. Artificial Intelligence (Ai) in Medical Diagnostics Market, By End User, 2021-2027
9.1.1. Hospitals
9.1.1.1. Market Revenue and Forecast (2016-2027)
9.1.2. Diagnostic Imaging Centers
9.1.2.1. Market Revenue and Forecast (2016-2027)
9.1.3. Diagnostic Laboratories
9.1.3.1. Market Revenue and Forecast (2016-2027)
9.1.4. Others
9.1.4.1. Market Revenue and Forecast (2016-2027)
Chapter 10.Global Artificial Intelligence (Ai) in Medical Diagnostics Market, Regional Estimates and Trend Forecast
10.1. North America
10.1.1. Market Revenue and Forecast, by Vehicle (2016-2027)
10.1.2. Market Revenue and Forecast, by Coating (2016-2027)
10.1.3. Market Revenue and Forecast, by Technology (2016-2027)
10.1.4. Market Revenue and Forecast, by Texture (2016-2027)
10.1.5. Market Revenue and Forecast, by Distribution Channel (2016-2027)
10.1.6. Market Revenue and Forecast, by Raw Material (2016-2027)
10.1.7. U.S.
10.1.7.1. Market Revenue and Forecast, by Vehicle (2016-2027)
10.1.7.2. Market Revenue and Forecast, by Coating (2016-2027)
10.1.7.3. Market Revenue and Forecast, by Technology (2016-2027)
10.1.7.4. Market Revenue and Forecast, by Texture (2016-2027)
10.1.8. Market Revenue and Forecast, by Distribution Channel (2016-2027)
10.1.8.1. Market Revenue and Forecast, by Raw Material (2016-2027)
10.1.9. Rest of North America
10.1.9.1. Market Revenue and Forecast, by Vehicle (2016-2027)
10.1.9.2. Market Revenue and Forecast, by Coating (2016-2027)
10.1.9.3. Market Revenue and Forecast, by Technology (2016-2027)
10.1.9.4. Market Revenue and Forecast, by Texture (2016-2027)
10.1.10. Market Revenue and Forecast, by Distribution Channel (2016-2027)
10.1.11. Market Revenue and Forecast, by Raw Material (2016-2027)
10.1.11.1.
10.2. Europe
10.2.1. Market Revenue and Forecast, by Vehicle (2016-2027)
10.2.2. Market Revenue and Forecast, by Coating (2016-2027)
10.2.3. Market Revenue and Forecast, by Technology (2016-2027)
10.2.4. Market Revenue and Forecast, by Texture (2016-2027)
10.2.5. Market Revenue and Forecast, by Distribution Channel (2016-2027)
10.2.6. Market Revenue and Forecast, by Raw Material (2016-2027)
10.2.7.
10.2.8. UK
10.2.8.1. Market Revenue and Forecast, by Vehicle (2016-2027)
10.2.8.2. Market Revenue and Forecast, by Coating (2016-2027)
10.2.8.3. Market Revenue and Forecast, by Technology (2016-2027)
10.2.9. Market Revenue and Forecast, by Texture (2016-2027)
10.2.10. Market Revenue and Forecast, by Distribution Channel (2016-2027)
10.2.10.1. Market Revenue and Forecast, by Raw Material (2016-2027)
10.2.11. Germany
10.2.11.1. Market Revenue and Forecast, by Vehicle (2016-2027)
10.2.11.2. Market Revenue and Forecast, by Coating (2016-2027)
10.2.11.3. Market Revenue and Forecast, by Technology (2016-2027)
10.2.12. Market Revenue and Forecast, by Texture (2016-2027)
10.2.13. Market Revenue and Forecast, by Distribution Channel (2016-2027)
10.2.14. Market Revenue and Forecast, by Raw Material (2016-2027)
10.2.14.1.
10.2.15. France
10.2.15.1. Market Revenue and Forecast, by Vehicle (2016-2027)
10.2.15.2. Market Revenue and Forecast, by Coating (2016-2027)
10.2.15.3. Market Revenue and Forecast, by Technology (2016-2027)
10.2.15.4. Market Revenue and Forecast, by Texture (2016-2027)
10.2.16. Market Revenue and Forecast, by Distribution Channel (2016-2027)
10.2.16.1. Market Revenue and Forecast, by Raw Material (2016-2027)
10.2.17. Rest of Europe
10.2.17.1. Market Revenue and Forecast, by Vehicle (2016-2027)
10.2.17.2. Market Revenue and Forecast, by Coating (2016-2027)
10.2.17.3. Market Revenue and Forecast, by Technology (2016-2027)
10.2.17.4. Market Revenue and Forecast, by Texture (2016-2027)
10.2.18. Market Revenue and Forecast, by Distribution Channel (2016-2027)
10.2.18.1. Market Revenue and Forecast, by Raw Material (2016-2027)
10.3. APAC
10.3.1. Market Revenue and Forecast, by Vehicle (2016-2027)
10.3.2. Market Revenue and Forecast, by Coating (2016-2027)
10.3.3. Market Revenue and Forecast, by Technology (2016-2027)
10.3.4. Market Revenue and Forecast, by Texture (2016-2027)
10.3.5. Market Revenue and Forecast, by Distribution Channel (2016-2027)
10.3.6. Market Revenue and Forecast, by Raw Material (2016-2027)
10.3.7. India
10.3.7.1. Market Revenue and Forecast, by Vehicle (2016-2027)
10.3.7.2. Market Revenue and Forecast, by Coating (2016-2027)
10.3.7.3. Market Revenue and Forecast, by Technology (2016-2027)
10.3.7.4. Market Revenue and Forecast, by Texture (2016-2027)
10.3.8. Market Revenue and Forecast, by Distribution Channel (2016-2027)
10.3.9. Market Revenue and Forecast, by Raw Material (2016-2027)
10.3.10. China
10.3.10.1. Market Revenue and Forecast, by Vehicle (2016-2027)
10.3.10.2. Market Revenue and Forecast, by Coating (2016-2027)
10.3.10.3. Market Revenue and Forecast, by Technology (2016-2027)
10.3.10.4. Market Revenue and Forecast, by Texture (2016-2027)
10.3.11. Market Revenue and Forecast, by Distribution Channel (2016-2027)
10.3.11.1. Market Revenue and Forecast, by Raw Material (2016-2027)
10.3.12. Japan
10.3.12.1. Market Revenue and Forecast, by Vehicle (2016-2027)
10.3.12.2. Market Revenue and Forecast, by Coating (2016-2027)
10.3.12.3. Market Revenue and Forecast, by Technology (2016-2027)
10.3.12.4. Market Revenue and Forecast, by Texture (2016-2027)
10.3.12.5. Market Revenue and Forecast, by Distribution Channel (2016-2027)
10.3.12.6. Market Revenue and Forecast, by Raw Material (2016-2027)
10.3.13. Rest of APAC
10.3.13.1. Market Revenue and Forecast, by Vehicle (2016-2027)
10.3.13.2. Market Revenue and Forecast, by Coating (2016-2027)
10.3.13.3. Market Revenue and Forecast, by Technology (2016-2027)
10.3.13.4. Market Revenue and Forecast, by Texture (2016-2027)
10.3.13.5. Market Revenue and Forecast, by Distribution Channel (2016-2027)
10.3.13.6. Market Revenue and Forecast, by Raw Material (2016-2027)
10.4. MEA
10.4.1. Market Revenue and Forecast, by Vehicle (2016-2027)
10.4.2. Market Revenue and Forecast, by Coating (2016-2027)
10.4.3. Market Revenue and Forecast, by Technology (2016-2027)
10.4.4. Market Revenue and Forecast, by Texture (2016-2027)
10.4.5. Market Revenue and Forecast, by Distribution Channel (2016-2027)
10.4.6. Market Revenue and Forecast, by Raw Material (2016-2027)
10.4.7. GCC
10.4.7.1. Market Revenue and Forecast, by Vehicle (2016-2027)
10.4.7.2. Market Revenue and Forecast, by Coating (2016-2027)
10.4.7.3. Market Revenue and Forecast, by Technology (2016-2027)
10.4.7.4. Market Revenue and Forecast, by Texture (2016-2027)
10.4.8. Market Revenue and Forecast, by Distribution Channel (2016-2027)
10.4.9. Market Revenue and Forecast, by Raw Material (2016-2027)
10.4.10. North Africa
10.4.10.1. Market Revenue and Forecast, by Vehicle (2016-2027)
10.4.10.2. Market Revenue and Forecast, by Coating (2016-2027)
10.4.10.3. Market Revenue and Forecast, by Technology (2016-2027)
10.4.10.4. Market Revenue and Forecast, by Texture (2016-2027)
10.4.11. Market Revenue and Forecast, by Distribution Channel (2016-2027)
10.4.12. Market Revenue and Forecast, by Raw Material (2016-2027)
10.4.13. South Africa
10.4.13.1. Market Revenue and Forecast, by Vehicle (2016-2027)
10.4.13.2. Market Revenue and Forecast, by Coating (2016-2027)
10.4.13.3. Market Revenue and Forecast, by Technology (2016-2027)
10.4.13.4. Market Revenue and Forecast, by Texture (2016-2027)
10.4.13.5. Market Revenue and Forecast, by Distribution Channel (2016-2027)
10.4.13.6. Market Revenue and Forecast, by Raw Material (2016-2027)
10.4.14. Rest of MEA
10.4.14.1. Market Revenue and Forecast, by Vehicle (2016-2027)
10.4.14.2. Market Revenue and Forecast, by Coating (2016-2027)
10.4.14.3. Market Revenue and Forecast, by Technology (2016-2027)
10.4.14.4. Market Revenue and Forecast, by Texture (2016-2027)
10.4.14.5. Market Revenue and Forecast, by Distribution Channel (2016-2027)
10.4.14.6. Market Revenue and Forecast, by Raw Material (2016-2027)
10.5. Latin America
10.5.1. Market Revenue and Forecast, by Vehicle (2016-2027)
10.5.2. Market Revenue and Forecast, by Coating (2016-2027)
10.5.3. Market Revenue and Forecast, by Technology (2016-2027)
10.5.4. Market Revenue and Forecast, by Texture (2016-2027)
10.5.5. Market Revenue and Forecast, by Distribution Channel (2016-2027)
10.5.6. Market Revenue and Forecast, by Raw Material (2016-2027)
10.5.7. Brazil
10.5.7.1. Market Revenue and Forecast, by Vehicle (2016-2027)
10.5.7.2. Market Revenue and Forecast, by Coating (2016-2027)
10.5.7.3. Market Revenue and Forecast, by Technology (2016-2027)
10.5.7.4. Market Revenue and Forecast, by Texture (2016-2027)
10.5.8. Market Revenue and Forecast, by Distribution Channel (2016-2027)
10.5.8.1. Market Revenue and Forecast, by Raw Material (2016-2027)
10.5.9. Rest of LATAM
10.5.9.1. Market Revenue and Forecast, by Vehicle (2016-2027)
10.5.9.2. Market Revenue and Forecast, by Coating (2016-2027)
10.5.9.3. Market Revenue and Forecast, by Technology (2016-2027)
10.5.9.4. Market Revenue and Forecast, by Texture (2016-2027)
10.5.9.5. Market Revenue and Forecast, by Distribution Channel (2016-2027)
10.5.9.6. Market Revenue and Forecast, by Raw Material (2016-2027)
Chapter 11. Company Profiles
11.1. Microsoft Corporation (US)
11.1.1. Company Overview
11.1.2. Product Offerings
11.1.3. Financial Performance
11.1.4. Recent Initiatives
11.2. NVIDIA (US)
11.2.1. Company Overview
11.2.2. Product Offerings
11.2.3. Financial Performance
11.2.4. Recent Initiatives
11.3. IBM (US)
11.3.1. Company Overview
11.3.2. Product Offerings
11.3.3. Financial Performance
11.3.4. Recent Initiatives
11.4. Intel (US)
11.4.1. Company Overview
11.4.2. Product Offerings
11.4.3. Financial Performance
11.4.4. Recent Initiatives
11.5. Siemens Healthineers (Germany)
11.5.1. Company Overview
11.5.2. Product Offerings
11.5.3. Financial Performance
11.5.4. Recent Initiatives
11.6. GE Healthcare (US)
11.6.1. Company Overview
11.6.2. Product Offerings
11.6.3. Financial Performance
11.6.4. Recent Initiatives
11.7. Digital Diagnostics (US)
11.7.1. Company Overview
11.7.2. Product Offerings
11.7.3. Financial Performance
11.7.4. Recent Initiatives
11.8. Xilinx (US)
11.8.1. Company Overview
11.8.2. Product Offerings
11.8.3. Financial Performance
11.8.4. Recent Initiatives
11.9. InformAI (US)
11.9.1. Company Overview
11.9.2. Product Offerings
11.9.3. Financial Performance
11.9.4. Recent Initiatives
11.10. Enlitic (US)
11.10.1. Company Overview
11.10.2. Product Offerings
11.10.3. Financial Performance
11.10.4. Recent Initiatives
11.11. Day Zero Diagnostics (US)
11.11.1. Company Overview
11.11.2. Product Offerings
11.11.3. Financial Performance
11.11.4. Recent Initiatives
11.12. Aidence (Netherlands)
11.12.1. Company Overview
11.12.2. Product Offerings
11.12.3. Financial Performance
11.12.4. Recent Initiatives
11.13. Butterfly Network, Inc. (US)
11.13.1. Company Overview
11.13.2. Product Offerings
11.13.3. Financial Performance
11.13.4. Recent Initiatives
11.14. Prognos (US)
11.14.1. Company Overview
11.14.2. Product Offerings
11.14.3. Financial Performance
11.14.4. Recent Initiatives
11.15. Zebra Medical Vision (Israel)
11.15.1. Company Overview
11.15.2. Product Offerings
11.15.3. Financial Performance
11.15.4. Recent Initiatives
11.16. Viz.ai (US)
11.16.1. Company Overview
11.16.2. Product Offerings
11.16.3. Financial Performance
11.16.4. Recent Initiatives
11.17. Quibin (Spain)
11.17.1. Company Overview
11.17.2. Product Offerings
11.17.3. Financial Performance
11.17.4. Recent Initiatives
11.18. Qure.ai (India)
11.18.1. Company Overview
11.18.2. Product Offerings
11.18.3. Financial Performance
11.18.4. Recent Initiatives
11.19. Therapixel (France)
11.19.1. Company Overview
11.19.2. Product Offerings
11.19.3. Financial Performance
11.19.4. Recent Initiatives
11.20. HeartFlow (US)
11.20.1. Company Overview
11.20.2. Product Offerings
11.20.3. Financial Performance
11.20.4. Recent Initiatives
Chapter 12. Research Methodology
12.1. Primary Research
12.2. Secondary Research
12.3. Assumptions
Chapter 13. Appendix
13.1. About Us
13.2. Glossary of Terms
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