Artificial Intelligence (Ai) in Medical Diagnostics Market 2021 Booming Across the Globe by Top Vendors Siemens Healthineers (Germany), GE Healthcare (US), Digital Diagnostics (US), Xilinx (US), InformAI (US)

ReportsnReports has recently added concise research on the "Artificial Intelligence (Ai) in Medical Diagnostics Market" is projected to reach USD 3,868 million by 2025 from USD 505 million in 2020, at a CAGR of 50.2% during the forecast period. Artificial Intelligence (Ai) in Medical Diagnostics Market by Component (Software, Service), Application (In Vivo, Radiology, OBGY, MRI, CT, Ultrasound, IVD), End-User (Hospital, Diagnostic Laboratory, Diagnostic Imaging Center) - Global Forecast to 2025

Market study of Artificial Intelligence (Ai) in Medical Diagnostics Market report considers a market attractiveness analysis, where each segment is benchmarked based on its market size, growth rate, and general attractiveness. This research report helps to understand the various drivers and restraints impacting the market during the forecast period. The report has been formed by using information from trustworthy sources such as journals, websites, and annual reports of the companies, white papers, and mergers. All of this collected data is then checked and validated by the market experts for the readers and end-users. The Artificial Intelligence (Ai) in Medical Diagnostics Market report has appropriate solutions to the complex business challenges and initiates an effortless decision-making process.

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Some of the prominent players operating in the AI in medical diagnostics market are:

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).

Market drivers, market restraints, opportunities and challenges are also evaluated in the Artificial Intelligence (Ai) in Medical Diagnostics Market report under market overview which gives helpful insights to businesses for taking the right moves. This market report is a great source of information for the major happenings and industry insights that support thriving in this competitive age. The report is prepared by taking into account the market type, organization volume, accessibility on-premises, end-users organization type, and availability at the global level in areas such as North America, South America, Europe, Asia-Pacific, Middle East and Africa. Moreover, estimation of strategic options, suggestions of winning action plans and support to make critical bottom-line decisions is also provided by experienced and innovative industry experts.

Software segment is expected to grow at the highest CAGR

On the basis of component, the AI in medical diagnostics market is segmented into software and services. The services segment dominated this market in 2020, while the software segment is estimated to grow at a higher CAGR during the forecast period. Software solutions help healthcare providers gain a competitive edge despite the challenges of being short-staffed and facing increasing imaging scan volumes. This is a key factor driving the growth of the software segment.

Hospitals to establish the largest market size of AI in medical diagnostics market

Based on end user, the AI in medical diagnostics market is segmented into hospitals, diagnostic imaging centers, diagnostic laboratories, and other end users. The hospitals segment commanded the largest share of 64.1% of this market in 2019. The large share of this segment can be attributed to the rising number of diagnostic imaging procedures performed in hospitals, the growing inclination of hospitals toward the automation and digitization of radiology patient workflow, increasing adoption of minimally invasive procedures in hospitals to improve the quality of patient care, and the rising adoption of advanced imaging modalities to improve workflow efficiency.

North America To Witness Significant Growth From 2020 To 2025

The AI in medical diagnostics market has been segmented into four main regional segments, namely, North America, Europe, the Asia Pacific, and the Rest of the World. In 2019, North America accounted for the largest market share of 37.6%. However, the APAC market is projected to register the highest CAGR of 53.2% during the forecast period, primarily due to the growth strategies adopted by companies in emerging markets, improved medical diagnostic infrastructure, increasing geriatric population, rising prevalence of cancer, and the implementation of favorable government initiatives.

Breakdown of supply-side primary interviews:

By Company Type: Tier 1 – 40%, Tier 2 – 30%, and Tier 3 – 30%
By Designation: C-level – 27%, Director-level – 18%, and Others – 55%
By Region: North America - 40%, Europe – 20%, APAC – 30%, Rest of the World – 10%

Research Coverage

This report studies the AI in medical diagnostics market based on component, end user, application, and region. The report also studies factors (such as drivers, restraints, opportunities, and challenges) affecting market growth. It analyzes the opportunities and challenges in the market and provides details of the competitive landscape for market leaders. Furthermore, the report analyzes micro markets with respect to their individual growth trends and forecasts the revenue of the market segments with respect to four main regions and respective countries.

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Key Benefits of Buying the Report

This report focuses on various levels of analysis—industry trends, market share of top players, and company profiles, which together form basic views and analyze the competitive landscape, and high-growth regions and their drivers, restraints, challenges, and opportunities. The report will help both established firms as well as new entrants/smaller firms to gauge the pulse of the market and garner greater market shares.

Table Of Contents

1 Introduction
1.1 Objectives Of The Study
1.2 Market Definition
1.3 Inclusions & Exclusions
1.3.1 Markets Covered
Figure 1 Ai In Medical Diagnostics Market Segmentation
1.3.2 Years Considered For The Study
1.4 Currency
1.5 Limitations
1.6 Stakeholders

2 Research Methodology
2.1 Research Data
2.2 Research Methodology Steps
Figure 2 Research Methodology: Ai In Medical Diagnostics Market
Figure 3 Research Design
2.2.1 Secondary Data
2.2.1.1 Key Data From Secondary Sources
2.2.2 Primary Data
Figure 4 Breakdown Of Primary Interviews: By Company Type, Designation, And Region
Figure 5 Primary Sources
2.2.2.1 Key Data From Primary Sources
2.3 Market Size Estimation Methodology
Figure 6 Research Methodology: Hypothesis Building
Figure 7 Market Size Estimation
2.4 Market Data Estimation And Triangulation
Figure 8 Data Triangulation Methodology
2.5 Assumptions For The Study
2.6 Covid-19-Specific Assumptions

3 Executive Summary
Figure 9 Ai In Medical Diagnostics Market, By Component, 2020 Vs. 2025 (Usd Million)
Figure 10 Ai In Medical Diagnostics Market, By Application, 2020 Vs. 2025 (Usd Million)
Figure 11 Ai In Medical Diagnostics Market, By End User, 2020 Vs. 2025 (Usd Million)
Figure 12 Geographical Snapshot Of The Ai In Medical Diagnostics Market

4 Premium Insights
4.1 Ai In Medical Diagnostics Market Overview
Figure 13 Influx Of Large And Complex Datasets In Healthcare To Drive Market Growth
4.2 North America: Ai In Medical Diagnostics Market, By Application And Country (2019)
Figure 14 In Vivo Diagnostic Applications Segment Accounted For The Largest Share Of The North American Market In 2019
4.3 Ai In Medical Diagnostics Market Share, By Application, 2020 Vs. 2025
Figure 15 In Vivo Diagnostic Applications Segment Will Continue To Dominate The Market In 2025
4.4 Ai In Medical Diagnostics Market: Geographic Growth Opportunities
Figure 16 Apac Market To Register The Highest Growth During The Forecast Period

5 Market Overview
5.1 Introduction
Figure 17 Ai In Medical Diagnostics Market: Drivers, Restraints, Opportunities, And Challenges
5.1.1 Drivers
5.1.1.1 Influx Of Large And Complex Datasets
5.1.1.2 Growing Number Of Cross-Industry Partnerships And Collaborations
5.1.1.3 Increasing Demand For Ai Tools In The Medical Imaging Field And Rising Focus On Reducing The Workload Of Radiologists
5.1.1.4 Government Initiative To Increase The Adoption Of Ai-Based Technologies
5.1.1.5 Growth In Funding For Ai-Based Start-Ups
5.1.2 Restraints
5.1.2.1 Reluctance Among Medical Practitioners To Adopt Ai-Based Technologies
5.1.2.2 Lack Of Skilled Ai Workforce And Ambiguous Regulatory Guidelines For Medical Software
5.1.3 Opportunities
5.1.3.1 Untapped Emerging Markets
5.1.3.2 Growing Potential Of Ai-Technology In Imaging & Diagnostics To Fight Covid-19
5.1.3.3 Increasing Focus On Developing Human-Aware Ai Systems
5.1.4 Challenges
5.1.4.1 Budgetary Constraints
5.1.4.2 Lack Of Curated Healthcare Data
5.1.4.3 Concerns Regarding Data Privacy
Figure 18 Types Of Healthcare Breaches Reported To The Us Department Of Health And Human Services (2018 To 2020)
5.1.4.4 Lack Of Interoperability Between Ai Solutions Offered By Different Vendors
5.2 Value Chain Analysis
Figure 19 Ai In Medical Diagnostics Market: Value Chain Analysis
5.3 Case Studies
5.3.1 Focus On Improving Workflow Efficacy And Reducing The Burden On Radiologists
5.3.1.1 Use Case 1: Reducing The Burden On Radiologists By Developing And Testing An Ai Model To Read Large Ultrasound Data
5.3.2 Improved Triage
5.3.2.1 Use Case 2: Precision Driven Health Developed Ml Model To Help Improve Work Triage Of Cardiologists (2019)
5.4 Impact Of Covid-19 On The Ai In Medical Diagnostics Market
Figure 20 Pre- And Post-Covid-19 Impact Analysis
5.5 Ecosystem Coverage
Figure 21 Ai In Medical Diagnostics Ecosystem
5.6 Technology Analysis
Table 1 Technological Developments By Leading Vendors
5.7 Regulations
5.7.1 Health Insurance Portability And Accountability Act Of 1996 (Hipaa)
5.7.2 Health Information Technology For Economic And Clinical Health Act Of 2009 (Hitech)
5.7.3 Consumer Privacy Protection Act Of 2017
5.7.4 National Cybersecurity Protection Advancement Act Of 2015
5.7.5 Future Of Life Institute’s Asilomar Ai Principles
5.7.6 The European Medical Devices Regulation (Eu) 2017/745 And In-Vitro Diagnostic Medical Devices Regulation (Eu) 2017/746 In Combination With The General Data Protection Regulation 2016/679
5.7.7 The Cybersecurity Law Of The People's Republic Of China
5.8 Pricing Analysis

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