AI in Healthcare: Global Market Analysis and Future Growth Trends

Published Date: January, 2019 || Pages: 130
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Overview of AI in Healthcare Market

Artificial Intelligence (AI) requires data mining approach as well as pattern recognition to medically diagnose the condition of a patient. Neural networks process information by recognizing patterns and data that has been previously loaded into the system. The AI in the healthcare market is expected to grow from USD ~2 billion in 2018 to USD ~36 billion by 2025, at a CAGR of ~50% during the forecast period. This is possible due to the competence of AI to recognize drug targets and help in drug design, discovery, identification, and screening of molecules instantly. Medical imaging, on the other hand, is one of the major application areas that has led to improvement in cancer and tumor diagnosis using AI. It is primarily based on pattern recognition that effectively works using deep learning technique.

The huge availability of big data, the growing number of cross-industry partnerships and collaborations is fuelling the growth of the AI market. In addition, demand to reduce the imbalance between the healthcare workforce and patients is further supplementing the growth of the AI in the healthcare market.

AI in Healthcare Market Opportunities

IEBS - Global AI in healthcare

Leading companies in the AI in healthcare market are NVIDIA (US), Intel (US), IBM (US), Google (US), Microsoft (US), AWS (US), General Vision (US), GE Healthcare (US), Siemens Healthineers (Germany), Medtronic (US). The market has active participation of start-ups. A few emerging start-ups in the market are CloudMedx (US), Imagia Cybernetics (Canada), Precision Health AI (US), and Cloud  Pharmaceuticals (US).

IEBS - AI in healthcare market trend

In 2015, there was a wave of 18 new doctor-facing companies resulting in a positive net increase of 6 companies. This balanced out the net decrease in the other main categories for a minimal decline in 2015 in terms of total new companies. Using the application called Machine vision which forms an integral part of Artificial intelligence, it is now possible to translate data and simulate human intelligence by using ADC (Analog to Digital Conversion) and DSP (Digital Signal Processing). Recent studies in the field of diagnostic AI include diagnosis of diseases like Alzheimer’s. Researchers at the University of California have reported that after analyzing over 1000 patients imaging data was translated that successfully predicted the presence of disease, six years prior to a physician’s diagnosis. Similar algorithms can be trained to identify protein lumps in the brain, abnormal cellular activities, and anomalies in the human system. This, in turn, would help intervene the disease at the much earlier stage.

IEBS - AI in helalthcare market share

North America accounted for the largest market share in the AI in the healthcare market in 2018. The wide-scale adoption of AI technologies across the continuum of care, especially in the US, is the key factor supporting the growth of the AI in the healthcare market in this region. APAC is expected to register the second-fastest growth rate as improving IT infrastructure, demand for affordable healthcare, and favorable government norms are expected to boost the growth of healthcare AI in the region.

1. Introduction
1.1. Objectives of the Study
1.2. Market Definition
1.3. Market Scope
1.4. Years Considered for the Study
1.5. Currency
1.6. Stakeholders

2. Research Strategy
2.1. Secondary Research
2.2. Primary Research
2.3. Market Engineering
2.4. Bottom-Up Approach
2.5. Top-Down Approach
2.6. Research Assumptions and Limitations

3. Executive Overview

4. AI Technology Segmentation/Platforms

5. AI in Different Healthcare Applications
5.1. Diagnostics & Medical Imaging
5.2. Consumer Integrated Health/IT solutions
5.3. Pharmaceutical/Drug Discovery

6. AI Platforms Penetration in Different Healthcare Applications

7. IP Scenario: AI in Healthcare
7.1. Key IP Players
7.2. Key Jurisdictions

8. Key Insights
8.1. Market Trends
8.2. Market Overview
8.2.1. Drivers
8.2.2. Restraints
8.2.3. Opportunities
8.2.4. Challenges
8.3. The ecosystem of AI in Healthcare Market
8.4. Case Studies

9. AI in Healthcare Market, By Offerings
9.1. Introduction
9.2. Hardware
9.2.1. Processor
9.2.2. Memory
9.2.3. Network
9.3. Software
9.3.1. AI Solutions
9.3.2. AI Platform
9.4. Services
9.4.1. Deployment & Integration
9.4.2. Support & Maintenance

10. AI in Healthcare Market, By Technology
10.1. Introduction
10.2. Machine Learning
10.3. Natural Language Processing
10.4. Context-Aware Computing
10.5. Computer Vision

11. AI in Healthcare Market, By Application
11.1. Introduction
11.2. Diagnostic Imaging
11.3. Robot-Assisted Surgery
11.4. Virtual Assistant
11.5. Inpatient Care & Hospital Management
11.6. Patient Data and Risk Analysis
11.7. Drug Discovery
11.8. Wearables
11.9. Research
11.10. Precision Medicine

12. AI in Healthcare Market, By End-User
12.1. Introduction
12.2. Hospitals and Providers
12.3. Patients
12.4. Pharmaceutical and Biotechnology Companies
12.5. Healthcare Payers

13. AI in Healthcare Market, By Region
13.1. North America
13.1.1. US
13.1.2. Canada
13.1.3. Mexico
13.2. Asia Pacific
13.2.1. China
13.2.2. India
13.2.3. Japan
13.2.4. South Korea
13.2.5. Rest of APAC
13.3. Europe
13.3.1. UK
13.3.2. France
13.3.3. Germany
13.3.4. Rest of Europe
13.4. RoW
13.4.1. Middle East and Africa
13.4.2. Africa
13.4.3. South America
13.4.4. Rest of RoW

14. Competitive Landscape
14.1. Overview
14.2. Leading Players in the AI in Healthcare Market
14.3. Partnerships, Agreements, and Collaborations
14.4. New Product Launches/Product Upgradations
14.5. Business Expansions
14.6. Venture Funding

15. Company Profiling
15.1. Nvidia
15.2. IBM
15.3. Microsoft
15.4. Intel
15.5. General Electric (GE)
15.6. Google
15.7. Siemens Healthineers (A Strategic Unit of the Siemens Group)
15.8. Medtronic
15.9. Amazon Web Services (AWS)
15.10. Micron Technology

16. Appendix
16.1. Market Insights
16.2. Questionnaire
16.3. Available Customizations
16.4. Authors

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