AI in healthcare market projected to grow at a CAGR of 44.9% from 2020 to 2026

The global AI in healthcare market is expected to grow from USD 4. 9 billion in 2020 and reach USD 45. 2 billion by 2026; it is projected to grow at a CAGR of 44. 9% during the forecast period.

New York, June 18, 2020 (GLOBE NEWSWIRE) -- announces the release of the report "Artificial Intelligence in Healthcare Market with Covid-19 Impact Analysis by Offering, Technology, End-Use Application, End User and Region - Global Forecast to 2026" -
The major factors driving the growth of the market are the increasing volume of healthcare data and growing complexities of datasets, the intensifying need to reduce towering healthcare costs, improving computing power and declining hardware costs, growing number of cross-industry partnerships and collaborations, and rising imbalance between health workforce and patients driving the need for improvised healthcare services.
Another major driving factor fueling the market growth currently is the adoption of this technology by multiple pharmaceutical and biotechnology companies across the world to expedite vaccine or drug development processes for COVID-19. The major restraint for the market is the reluctance among medical practitioners to adopt AI-based technologies and lack of skilled workforce.

MPU processor segment expected to hold largest share in AI in healthcare in 2020
An MPU contains all or most of the CPU functions and is the engine that goes into motion when the computer is on.A microprocessor is specially designed to perform arithmetic and logic operations that use small number-holding areas called registers.

Typical microprocessor operations include adding, subtracting, comparing two numbers, and fetching numbers. These operations are the result of a set of instructions that are part of the microprocessor design.

AI in healthcare market for machine learning projected to grow at highest CAGR during forecast period
Growing adoption of deep learning in various healthcare applications, especially in the areas of medical imaging, disease diagnostics, and drug discovery, and the use of different sensors and devices to track a patient’s health status in real time are supplementing the growth of the market.

Patient data & risk analysis segment to capture largest share of AI in healthcare market
The growth of the patient data & risk analysis segment is attributed to the increasing adoption of EMRs and various advantages offered by AI systems to healthcare service providers, patients, pharmaceuticals companies, and payers.

Breakdown of profiles of primary participants:
• By Company Type: Tier 1 – 40%, Tier 2 – 25%, and Tier 3 – 35%
• By Designation: C-level Executives – 45%, Directors – 25%, and Others – 30%
• By Region: North America – 55%, Europe – 15%, Asia Pacific (APAC)– 20%, and the Rest of the World (RoW) – 10%

Major players in the AI in healthcare market are NVIDIA Corporation (NVIDIA) (US), Intel Corporation (Intel) (US), International Business Machines Corporation (IBM) (US), Google Inc. (Google) (US), Microsoft Corporation (Microsoft) (US), Amazon Web Services (an, Inc. subsidiary) (AWS) (US), General Vision, Inc. (US), General Electric (GE) Healthcare (US), Siemens Healthineers (Germany), Medtronic plc (US), Johnson & Johnson Services, Inc. (Johnson & Johnson) (US), and Koninklijke Philips N.V. (Netherlands).

Research Coverage:
The AI in healthcare market has been segmented based on offering, technology, end-use application, and end user. It also provides a detailed view of the market across 4 main regions: North America, Europe, APAC, and RoW.

Reasons to Buy the Report:
• This report includes statistics pertaining to the AI in healthcare market based on offering, technology, end-use application, end user, and geography.
• This report includes detailed information on major drivers, restraints, opportunities, and challenges pertaining to the AI in healthcare market.
• The report includes illustrative segmentation, analysis, and forecast for the AI in healthcare market based on its segments and subsegments.
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