Global Healthcare Artificial Intelligent Market : Insights and Forecast, 2018-2025: Emphasis on Technology (Machine Learning, Deep Learning, Artificial Neural Network), Applications (Robotic Surgery, Diagnosis, Virtual Nursing Assistance, Administrative Workflow Assistance); Offerings (Hardware, Software and Services) and Region
- UNI3007740
- 127 Pages
- March 2019
- ICT & Media
Artificial Intelligence is the development of computer systems that are able to perform tasks that would require human intelligence with much higher precisions and error control than that done by humans. AI facilitates in creation of intelligent agents where an intelligent agent is a system that recognizes its environment of operation and takes actions which maximizes its likelihood of success. The importance of AI in healthcare was realised in early 1980s when the absence of proper data management and requirement of extreme precision along with importance of minimal invasive methods was recognised. Artificial intelligence is a branch of computer science and information technology that is capable of analysing complex medical data. Today, in the age of breakthrough of technology and automation, the research and implementation of AI in healthcare is at its best. Healthcare sector is one of the most important sectors that is a priority for the human race. Owing to its amalgamation with the IT industry, the growth and development of healthcare industry has increased and reached the next level.
Recent Developments under Computing Power in Healthcare
Key Developments Key Insights
IBM Watson for Oncology • IBM have developed Watson technologies for healthcare. It is a unified platform meant to assist doctors and healthcare professionals in various aspects of treatment. IBM Watson for Oncology is specifically designed for helping oncologists involved in cancer treatment
• Watson for Oncology derives data from various sources including MSK curated literature and rationales, as well as over 290 medical journals, over 200 textbooks, and 12 million pages of text
IBM and Manipal Hospitals (India) • In India, IBM has partnered with Manipal Hospitals to provide diagnosis and treatment to cancer patients. Watson for Oncology is used across 16 facilities and academic centers of the hospital where more than 200,00 patients are treated each year
American Cancer Society and IBM • The American Cancer Society is utilizing IBM Watson to mine data from websites and relevant sources to offer personalized treatments for oncology patients. According to IBM, over 16 oncology practices are depending on Watson to enable doctors in translating DNA insights into personalized treatment for patients
Dartmouth-Hitchcock and Microsoft • Dartmouth-Hitchcock, a US-based health system based in New Hampshire has adopted Microsoft’s Cortana Intelligence Suite to predict medical emergencies for patients. Branded as ImagineCare, this solution is available to more than 6000 patients of Dartmouth
Microsoft India and L V Prasad Eye Institute • Microsoft India has partnered with L V Prasad Eye Institute to launch a consortium named Microsoft Intelligent Network for Eyecare (MINE). The partner organizations of this consortium would include Bascom Palmer (University of Miami), Flaum Eye Institute (University of Rochester (USA)), Federal University of Sao Paulo (Brazil) and Brien Holden Vision Institute (Australia). These organizations will collaborate on the diverse patient dataset to evolve machine learning predictive models for vision impairment and eye disease
Pfizer and IBM • Pfizer is using IBM’s Watson machine-learning platform to help find new immuno-oncology targets and drugs
Sanofi and Exscientia • Sanofi is using a rival system from UK firm Exscientia in a metabolic disease program
The outburst of technology that is digitally enabled, wireless connectivity across increasingly mobile devices has created an increasing democratisation of access for healthcare. Some of the most powerful AI tools are already embedded in Android or iOS. This technology is providing consumers with the data and information they need to proactively manage their own health and wellness, and to make better, more informed decisions in partnership with their healthcare providers. AI can prove to be a boom in the field of diagnosis. The high cost involved in diagnostic processes, over-testing of low-risk patients, and limited capability for early detection of chronic diseases are driving the adoption of AI in diagnostics. This is because AI is capable of bridging the gap between doctor-centric diagnosis and AI-based diagnosis through pattern recognition and machine learning technologies.
Coming to drug development, it requires lots of time, investment and resources. Owing to this, the pharma companies are keen to embrace digital transformation and AI. According to Deloitte, in 2017, 12 largest biopharma companies received just 3.2% returns from their drug-research units, as against 10% in 2010. The use of AI in drug discovery is expected to expedite the overall process. Applied intelligence can improve drug discovery success rates by 8-10%, resulting in savings worth billions of dollars for the industry. Finding drug discovery compounds and precision medicine are the major trending applications over other pharma based AI applications.
“Machine learning technology of AI dominated the market globally in 2018 and is expected to maintain its lead in 2025”
Based on technology, the global AI in healthcare market has been segmented into machine learning, deep learning and artificial neural network. Out of these technologies, in 2018, machine learning dominated the market globally and is expected to maintain its lead in 2025. The increasing power of machine learning in diagnosing disease and in categorisation and classifying health data is empowering physicians and speed-up decision making across the medical facilities including hospitals or clinic.
“Amongst application, robotic surgery holds the major share globally in 2018 but diagnosis has been estimated to lead the market during the forecast period.”
Based on technology, the global AI in healthcare market has been segmented into robotic surgery, diagnosis, Virtual Nursing assistance and Administrative workflow assistance. In 2018, robotic surgery dominated the application segment of global AI in healthcare market, generating revenue of US$8589 million, followed by virtual nursing assistance and administrative workflow. The segment is expected to grow at a CAGR of XX% during the forecast period by 2025. However, the diagnosis segment is expected to witness the highest CAGR of XX% during the analysed period.
“Amongst end users, hardware segment has been anticipated to dominate the AI in healthcare sector by 2025.”
Based on the type of offering, the global AI in healthcare market is segmented into hardware, software or services. Currently, services segment dominates the market. However, hardware segment is expected to witness the highest CAGR growth during the forecast period 2018-2025.
“North America region holds the highest market share in 2018 but Asia Pacific market has been expected to witness the highest market growth in the forecast period”
Artificial intelligence in healthcare market in North America has been on an up-surging trend due to the high adoption rate of AI in country such as the US and Canada, paired with development and growth of research & development activities that combine the investments by government and private organizations. As far as Asia-Pacific region is concerned, it has lagged behind North America and Europe in terms of technology adoption. However, AI is one technology area where Asia-Pacific can stand apart, compared to other region and has been expected to witness the highest growth in the forecast period.
Competitive Landscape-Top 10 Market Players
Medtronic Plc, Abbott Laboratories, Johnson and Johnson, Bcton Dickinson, Boston Scientific Corporation, Koninklijke Philips N.V, Roche Holding AG, Siemens Healthineers AG, Stryker Corporation and Oracle Corporation are the major players operating in the AI in healthcare market. These company are partnering up with technology leaders and are investing heavily to come up with new and innovative AI backed healthcare equipment to treat patients.
Reasons to buy:
• The dental imaging market study presents the current market size, trend, forecast until 2024. The analysis presented in the report is a combination of deep dive secondary research and input from Key Opinion Leaders of the industry
• The report presents a quick review of overall industry performance at one glance
• The report covers in-depth analysis of prominent industry peer with a primary focus on key business financials, product portfolio, expansion strategies, and recent developments
• Detailed examination on drivers, restraints, key trends and opportunities prevailing in the industry
• Examination of industry attractiveness with the help of Porter’s Five Forces analysis
• The study comprehensively covers the market across different segments and sub segments
• Deep dive regional level analysis of the industry
Customization Options:
The Dental Imaging Technology Market can be customized to the country level or any other market segment. Besides this, UMI understands that you may have your own business need, hence we also provide fully customized solutions to clients.
1.1 Market Definition 12
1.2 Objective of the Study 12
1.3 Limitation 12
1.4 Stakeholders 13
1.5 Currency used in the Report 13
2. RESEARCH METHODOLOGY OR ASSUMPTION 14
2.1 Research Methodology for AI in Healthcare Market 14
2.1.1 Main objective of the AI in health care sector Market Study 15
3. REGULATORY FRAMEWORK AND KEY DEVELOPMENT 16
3.1 General Overview 16
3.1.1 North America 16
3.1.1.1 North America Regulatory Framework for AI in Healthcare 16
3.1.1.2 North American Key Developments of AI in Healthcare 17
3.1.2 Europe 17
3.1.2.1 European Regulatory Framework for AI in Healthcare 17
3.1.2.2 European Key Developments of AI in Healthcare 18
3.1.3 Asia Pacific (APAC) 19
3.1.3.1 Asia Pacific (APAC) Regulatory Framework for AI in Healthcare 19
3.1.3.2 Asia Pacific (APAC) Key Developments of AI in Healthcare 20
3.1.4 Rest of World (RoW) 20
3.1.4.1 Rest of World (RoW) Regulatory Framework for AI in Healthcare 20
4. INDUSTRY PERFORMANCE 22
5. EXECUTIVE SUMMARY 23
6. MARKET OVERVIEW 25
6.1 Introduction 25
6.2 Market Dynamics 26
6.2.1 Market Drivers 26
6.2.1.1 Increasingly Large and Complex Data Set 26
6.2.1.2 Growing Demand to Reduce Healthcare Costs 28
6.2.1.3 Improving Computing Power in Healthcare 29
6.2.1.4 Rising Need for Improvised Healthcare Services 30
6.2.1.5 Application of AI for novel surgeries and screening 31
6.2.2 Market Restraints 33
6.2.2.1 Limitations of AI decision-making 33
6.2.2.2 Reluctance Among Medical Practitioners to Adopt AI-Based Technologies 33
6.2.2.3 Lack of Skilled AI Workforce and Ambiguous Regulation for Medical Software 34
6.2.3 Trends in AI in Healthcare 34
6.2.3.1 Democratisation of access 34
6.2.3.2 Migration from Doctor-Centric Diagnostics to Data-Driven Diagnostics 34
6.2.3.3 Transformation of Drug Discovery in Pharma Industry 34
6.2.3.4 Data Explosion 35
6.2.4 Opportunity 35
6.2.4.1 Growing Potential of AI-Based Tools 35
6.2.4.2 Increasing Focus on Developing Human-Aware AI Systems 35
6.2.4.3 Surging Spending Power on R&D 36
6.2.4.4 Untapped market in developing regions 37
7. KEY MARKET INDICATORS 38
7.1 General Overview 38
7.1.1 Demand and Supply Side Analysis 38
7.1.2 North America 39
7.1.3 Europe 39
7.1.4 Asia-Pacific 39
7.1.5 Applications of AI in Healthcare 41
7.1.5.1 Top Winning Strategies 41
7.1.5.1.1 Top Product launches 42
7.1.5.1.2 Top Investments 43
7.1.5.1.3 Top Acquisition and Collaborations 45
8. MARKET INSIGHTS, BY TECHNOLOGY 46
8.1 General Overview 46
8.1.1 Machine Learning 47
8.1.2 Deep Learning 48
8.1.3 Artificial Neural Network 49
9. MARKET INSIGHTS, BY APPLICATION 52
9.1 General Overview 52
9.1.1 Robotic Surgery 53
9.1.2 Diagnosis 54
9.1.3 Virtual Nursing Assistance 55
9.1.4 Administrative Workflow Assistance 56
10. MARKET INSIGHTS, BY TYPE OF OFFERINGS 58
10.1 General Overview 58
10.1.1 Hardware 59
10.1.2 Software 60
10.1.3 Services 62
11. MARKET INSIGHTS, BY REGION 64
11.1 General Overview 64
11.2 North America Healthcare AI Market 65
11.2.1 North America Healthcare AI Market, by Technology 65
11.2.2 North America Healthcare AI Market, by Application 66
11.2.3 North America Healthcare AI Market, by Type of Offerings 68
11.3 Europe Healthcare AI Market, USD Million (2015-2025) 68
11.3.1 Europe Healthcare AI Market, by Technology 69
11.3.2 Europe Healthcare AI Market, by Application 70
11.3.3 Europe Healthcare AI Market, by Type Offering 71
11.4 Asia-Pacific Healthcare AI Market, USD Million (2015-2025) 71
11.4.1 Asia-Pacific Healthcare AI Market, by Technology 72
11.4.2 Asia-Pacific Healthcare AI Market, by Application 73
11.4.3 Asia-Pacific Healthcare AI Market, by Type of Offerings 74
11.5 Rest of the World Healthcare AI Market, USD Million (2015-2025) 74
11.5.1 Rest of World Healthcare AI Market, by Technology 75
11.5.2 Rest of World Healthcare AI Market, by Application 76
11.5.3 Rest of World Healthcare AI Market, by Type of Offerings 77
12. COMPETITIVE SCENARIO 78
12.1 Global Healthcare AI Market Share Analysis, 2018 78
12.2 Porter’s Five forces analysis 80
12.2.1 Bargaining power of Buyer 80
12.2.2 Bargaining power of Supplier 81
12.2.3 Threat of new entrants 81
12.2.4 Availability of Substitute 82
12.2.5 Industry Rivalry 82
13. TOP COMPANY PROFILES 83
13.1 Medtronic Plc 83
13.1.1 Key Facts 83
13.1.2 Business Description 83
13.1.3 Key Product/Services Offerings 84
13.1.4 SWOT Analysis 85
13.1.5 Key Financials 85
13.1.5.1 Revenue Split 86
13.1.6 Recent Developments 86
13.1.7 Funding 87
13.2 Abbott Laboratories 88
13.2.1 Key Facts 88
13.2.2 Business Description 88
13.2.3 Key Product/Services Offerings 89
13.2.4 SWOT Analysis 89
13.2.5 Key Financials 90
13.2.5.1 Revenue Split 90
13.2.6 Recent Developments 91
13.3 Johnson & Johnson 92
13.3.1 Key Facts 92
13.3.2 Business Description 92
13.3.3 Key Product/Services Offerings 93
13.3.4 SWOT Analysis 93
13.3.5 Key Financials 94
13.3.5.1 Revenue Split 94
13.3.6 Recent Developments 95
13.4 Becton Dickinson 97
13.4.1 Key Facts 97
13.4.2 Business Description 97
13.4.3 Key Product/Services Offerings 98
13.4.4 SWOT Analysis 99
13.4.5 Key Financials 99
13.4.5.1 Revenue Split 100
13.4.6 Recent Developments 100
13.5 Boston Scientific Corporation 101
13.5.1 Key Facts 101
13.5.2 Business Description 101
13.5.3 Key Product/Services Offerings 102
13.5.4 SWOT Analysis 103
13.5.5 Key Financials 103
13.5.5.1 Revenue Split 104
13.5.6 Recent Developments 104
13.6 Koninklijke Philips N.V. 105
13.6.1 Key Facts 105
13.6.2 Business Description 105
13.6.3 Key Product/Services Offerings 106
13.6.4 SWOT Analysis 106
13.6.5 Key Financials 107
13.6.5.1 Revenue Split 107
13.6.6 Recent Developments 108
13.6.7 Funding 108
13.7 Roche Holding AG 109
13.7.1 Key Facts 109
13.7.2 Business Description 109
13.7.3 Key Product/Services Offerings 110
13.7.4 SWOT Analysis 111
13.7.5 Key Financials 111
13.7.5.1 Revenue Split 112
13.7.6 Recent Developments 113
13.7.7 Funding 113
13.8 Siemens Healthineers AG. 114
13.8.1 Key Facts 114
13.8.2 Business Description 114
13.8.3 Key Product/Services Offerings 115
13.8.4 SWOT Analysis 115
13.8.5 Key Financials 116
13.8.5.1 Revenue Split 116
13.8.6 Recent Developments 117
13.9 Stryker Corporation 118
13.9.1 Key Facts 118
13.9.2 Business Description 118
13.9.3 Key Product/Services Offerings 119
13.9.4 SWOT Analysis 120
13.9.5 Key Financials 120
13.9.5.1 Revenue Split 121
13.9.6 Recent Developments 121
13.10 Oracle Corporation 122
1.1.1 Key Facts 122
1.1.2 Business Description 122
1.1.3 Key Product/Services Offerings 123
1.1.4 SWOT Analysis 124
1.1.5 Key Financials 124
1.1.6 Revenue Split 125
1.1.7 Recent Developments 125
TABLE 2 Recent Developments under Computing Power in Healthcare 29
TABLE 3 Recent Top Funding’s in AI based Healthcare Start-Ups 44
TABLE 4 Global Machine Learning Market Size, by Region USD Billion (2014-2025) 48
TABLE 5 Deep Learning market, USD Billion (2015-2025) by Region 49
TABLE 6 Artificial Neural Network market, USD Billion (2015-2025) by Region 51
TABLE 7 Global AI Robotic Surgery Market Size, by Region 2018-2025 (USD Billion) 54
TABLE 8 Global AI Diagnosis Market Size, by Region 2018-2025 (USD Billion) 55
TABLE 9 Global AI Virtual Nursing Assistance Market Size, by Region 2018-2025 (USD Billion) 56
TABLE 10 Global AI Administrative Workflow Assistance Market Size, by Region 2018-2025 (USD Billion) 57
TABLE 11 Global Healthcare AI Hardware Market Size, by Region 2018-2025 (USD Billion) 59
TABLE 12 Global Healthcare AI Software Market Size, by Region 2018-2025 (USD Billion) 61
TABLE 13 Global Healthcare AI Services Market Size, by Region 2018-2025 (USD Billion) 63
TABLE 14 Global Healthcare AI Market, USD Billion (2014-2024) by Region 64
TABLE 15 Medtronic Plc Key Facts 83
TABLE 16 Product segmentation of Medtronic Plc 84
TABLE 17 Medtronic plc Growth Strategy 84
TABLE 18 Medtronic Plc financials, US$ Mn (2013-2018) 85
TABLE 19 Abbott Laboratories Key Facts 88
TABLE 20 Product segmentation of Abbott Laboratories 89
TABLE 21 Abbott laboratories Growth Strategy 89
TABLE 22 Abbott Laboratories Financials, US$ Mn (2013-2017) 90
TABLE 23 Johnson & Johnson Key Facts 92
TABLE 24 Product segmentation of Johnson & Johnson 93
TABLE 25 Johnson & Johnson Growth Strategy 93
TABLE 26 Johnson & Johnson Financials, US$ Mn (2013-2017) 94
TABLE 27 Research & Development Expense US$ Mn (2015-2017) 95
TABLE 28 Becton Dickinson Key Facts 97
TABLE 29 Product segmentation of Becton Dickinson 98
TABLE 30 Becton Dickinson Growth Strategy 98
TABLE 31 Becton Dickinson financials, US$ Mn (2013-2017) 99
TABLE 32 Boston Scientific Corporation Key Facts 101
TABLE 33 Product segmentation of Boston Scientific Corporation 102
TABLE 34 Boston Scientific Corporation Growth Strategy 102
TABLE 35 Boston Scientific Corporation Financials, US$ Mn (2013-2017) 103
TABLE 36 Koninklijke Philips N.V. Key Facts 105
TABLE 37 Product segmentation of Philips 106
TABLE 38 Philips Growth Strategy 106
TABLE 39 Philips Financials, US$ Mn (2013-2017) 107
TABLE 40 Roche Key Facts 109
TABLE 41 Product segmentation of Roche 110
TABLE 42 Roche Growth Strategy 110
TABLE 43 Roche Financials, US$ Mn (2013-2017) 111
TABLE 44 Siemens Healthcare AG Key Facts 114
TABLE 45 Product segmentation of Siemens Healthcare 115
TABLE 46 Siemens Healthcare Growth Strategy 115
TABLE 47 Siemens Healthcare Financials, US$ Mn (2015-2018) 116
TABLE 48 Stryker Corporation Key Facts 118
TABLE 49 Product segmentation of Stryker Corporation 119
TABLE 50 Stryker Corporation Growth Strategy 119
TABLE 51 Stryker Corporation Financials, US$ Mn (2013-2017) 120
TABLE 52 Oracle Corporation Key Facts 122
TABLE 53 Product segmentation of Oracle Corporation 123
TABLE 54 Oracle Growth Strategy 123
TABLE 55 Oracle Financials, US$ Mn (2013-2018) 124
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