Artificial Intelligence in Healthcare Market Global Trends, Market Share, Industry Size, Growth, Opportunities, and Market Forecast 2019 to 2029 Global Artificial Intelligence in Healthcare Market is estimated to value over USD 37 billion by 2029 end and is expected to register a CAGR of over 50% during the forecast period 2019 to 2029. The artificial intelligence (AI) is capable of improving patient outcomes by accurately identifying the source cause of the disease, this is positively influencing the market growth. Furthermore, there has been a remarkable rise in venture capital investments in AI technology which bolsters the market growth. Additionally, the growing importance of big data in healthcare is expected to boost market growth. The data generated in the healthcare industry is consistently mounting and to efficiently manage this ever-increasing volume of big data, the adoption of artificial intelligence becomes crucial and this is predicted to augment the market growth significantly. For example, Google recently launched its healthcare project, Google Deepmind Health, which can be efficiently used for collecting, storing and normalizing healthcare database. These innovative projects that are supported or initiated by tech giants will propel market growth. The use of AI-based tools for elderly care has a high potential of showcasing significant market growth during the forecast period. Moreover, markets like China and India are unexplored and have untapped potential thus presenting lucrative opportunities for the market to proliferate. Nevertheless, a dearth of skilled labour for implementing AI technology and imprecise regulatory scenario are some factors that can impede the market growth. Insights on Global Artificial Intelligence in Healthcare: Natural Language Processing Predicted to Prove Key to Effective Decision-making in Healthcare Industry Natural language processing (NLP) algorithm has a plethora of applications in healthcare industry. It can enhance the wholeness and comprehensibility of electronic health records by translating unbound text into standardised data. NLP can fill semantic data lakes and data warehouses with relevant information that can be accessed by free-text query user interfaces. Additionally, it can manage documentation requirements very efficiently by permitting providers with the authority of generating customised educational materials for patients that are ready to be discharged. These factors are instrumental in proliferating the growth of this segment. Deep learning technology segment has untapped potential and is capable of recording high market numbers during the forecast period. Currently, deep learning is mainly used in small-scale research projects, before these projects enter the commercialization stage. Nonetheless, deep learning is gradually finding its way into newer and innovative tools that have applications of the highest value in the realworld clinical environment. Convolution neural networks (CNNs), a type of deep learning, is appropriate for analysing images like X-rays or MRI results. CNNs are designed in a way that they can efficiently process images thus permitting the networks to handle and operate larger images. This has resulted into CNNs surpassing the accuracy of human diagnosticians when it comes to identifying important imaging features in diagnostic studies. The software segment dictates the market due to consistent innovations catering to the requirement of healthcare sector. The hardware segment is projected to showcase significant market growth during the forecast period. Asia Pacific Region is a Lucrative Market and is Projected to Witness Remarkable Growth During the Forecast Period The Asia Pacific market has untapped potential owing to the massive investments in research and development and rapid integration of AI technology in the healthcare infrastructure of the region. Furthermore, an ever-increasing patient population shall stimulate demand for better healthcare facilities and an improved healthcare infrastructure which will further bolster the growth of the market. Drug Discovery Application Shall Showcase Noteworthy Market Growth Drug discovery application is anticipated to exhibit remarkable market growth during the forecast period. The integration of AI technology in drug discovery will help lessen the production costs required for developing new drugs. Recently, Berg, a Boston-based AI specialist company, collaborated with Astra Zeneca for drug discovery. Such partnerships shall positively influence the proliferation of the market. Key Market Players: • IBM (Watson Health) • AiCure • APIXIO Inc. • iCarbonX • Insilico Medicine Inc. • Sophia Genetics • Welltok • Zebra Medical Vision Ltd. IBM Watson is an ideal example of a machine-learning NLP technology in the healthcare industry. It has a huge appetite for gathering academic literature and it is gaining expertise in clinical decision support (CDS) for cancer care and precision medicine. In 2014, IBM partnered with EHR developer Epic and the Carillion clinic located in Virginia to investigate how machine learning and NLP could be utilised for warning patients suffering from heart disease. this collaboration took place even before IBM set up a dedicated Watson health division. The system not only highlighted pertinent clinical data but also identified behavioural and social factors that are recorded in the clinical note but somehow don’t make it into the structured EHR template. Like for instance, the system checks the mental status of the patient by verifying whether the patient is depressed or not. Using its machine learning capabilities, the Watson system also identifies the living status of the patient like checking the financial status of the patient. Watson acquired a database of around 21 million records in just six weeks and achieved an accuracy rate of close to 85% for patient identification which is remarkable considering the short period it took for processing such a huge volume of database. Request a Sample Report @ https://www.futurewiseresearch.com/requestsample.aspx?id=2296&page=requestsample Global Artificial Intelligence in Healthcare Market Segmentation: 1. By Region • North America • Europe • Asia Pacific • Latin America • Rest of the World 2. By Technology • Natural Language Processing (NLP) • Machine Learning o Deep Learning o Supervised Learning o Unsupervised Learning o Reinforcement Learning • Context-Aware Computing • Computer Vision 3. By Offering • Software • Hardware o Processor o Memory • Services o Deployment & Integration o Support & Maintenance 4. By End-Use Application • In-Patient Care & Hospital • Patient Data and Risk Analysis • Medical Imaging & Diagnostics • Lifestyle Management & Monitoring • Virtual Assistant • Healthcare Assistant Robots • Wearable • Mental Health 5. • • • • By End User Patients Hospitals Biotechnology Companies High-tech Hospitals and Research Labs Purchase a Copy & Ask For Discount: https://www.futurewiseresearch.com/requestsample.aspx?id=2296&page=askfordiscount Competitive Landscape: • Tier 1 players- established companies in the market with a major market share • Tier 2 players • Emerging players which are growing rapidly • New Entrants FutureWise Key Takeaways: • With an ever-increasing patient population, the healthcare database volume shall be consistently increasing thus making the AI technology more crucial for database management • Deep learning technology is currently at its nascent stage and further advancements in this technology shall expand the market significantly Objectives of the Study: • To provide with an exhaustive analysis on the artificial intelligence in healthcare market by region, by technology, by offering, by end-use application, by end user • To cater comprehensive information on factors impacting market growth (drivers, restraints, opportunities, and industry-specific restraints) • To evaluate and forecast micro-markets and the overall market • To predict the market size, in key regions (along with countries)— North America, Europe, Asia Pacific, Latin America and rest of the world • To record evaluate and competitive landscape mapping- product launches, technological advancements, mergers and expansions • Profiling of companies to evaluate their market shares, strategies, financials and core competencies Table of Contents 1. Introduction 1.1. Scope and Objective 1.2. Assumptions and Acronyms 1.3. Forecast Factors 1.4. Research Methodology 2. Executive Summary 2.1. Industry Cluster Analysis 2.2. Competition Matrix 2.3. Strategies Recommendations 3. Market Definition 3.1. Report Scope (Inclusions & Exclusions) 3.2. Market Segmentation 4. Global Artificial Intelligence in Healthcare Market Overview 4.1. Global Artificial Intelligence in Healthcare Market Revenue (USD Mn) 5. Key Inclusions 5.1. Porter’s Five Force analysis 5.2. Market Dynamics 5.3. Industry Trends 5.4. Regulatory Guidelines 5.5. Opportunities for Artificial Intelligence in Healthcare Market 6. Competition Dynamics 6.1. Company Share Analysis (2019) 7. Global Artificial Intelligence in Healthcare Market Revenue (USD Mn), 2019-2029 by Technology 7.1. Key Market Findings 7.2. Machine Learning 7.2.1 Deep Learning 7.2.2 Supervised Learning 7.2.3 Reinforcement Learning 7.2.4 Unsupervised Learning 7.3. Natural Language Processing 7.4. Context-Aware Computing 7.5. Computer Vision 8. Global Artificial Intelligence in Healthcare Market Market Revenue (USD Mn), 2019-2029 by End Use Application 8.1. Key Market Findings 8.2. Inpatient Care & Hospital 8.3. Patient Data and Risk Analysis 8.4. Medical Imaging & Diagnostics 8.5. Lifestyle Management & Monitoring 8.6. Virtual Assistant 8.7. Healthcare Assistance Robots 8.8. Wearable 8.9. Mental Health 9. Global Artificial Intelligence in Healthcare Market Revenue (USD Mn), 2019-2029 by Offering 9.1. Key Market Findings 9.2. Hardware (Processor, Memory) 9.3. Computing Architecture (Network) 9.4. Software 9.5. Solutions (Cloud, AI Platform, Own ML Frameworks) 10. Global Artificial Intelligence in Healthcare Market Revenue (USD Mn), 20192029 by End User 10.1. Key Market Findings 10.2. Patients 10.3. Hospitals and Providers 10.4. Biotechnology Companies 10.5. High tech Hospitals and Research labs (Healthcare Assistance Robots) 11. Global Artificial Intelligence in Healthcare Market Revenue (USD Mn), 20192029 by Region 11.1. Key Market Findings 11.2. Long Term ROI Segments 11.3. Revenue Opportunity Influencing Factors 11.4. Market Revenue (USD Mn) Assessment and Forecast by Region,2029 11.4.1 North America 11.4.2 Latin America 11.4.3 Europe 11.4.4 Asia Pacific 11.4.5 Rest of world 12. North America Artificial Intelligence in Healthcare Market Revenue (US$ Mn), 2019-2029 12.1. Key Market Findings 12.2. Long Term ROI Segments 12.3. Revenue Opportunity Influencing Factors 12.4. Market Revenue (USD Mn) Assessment and Forecast by Country, 2019-2029 12.4.1 US 12.4.2 Canada 13. Latin America Artificial Intelligence in Healthcare Market Revenue (US$ Mn), 2019-2029 13.1. Key Market Findings 13.2. Long Term ROI Segments 13.3. Revenue Opportunity Influencing Factors 13.4. Market Revenue (USD Mn) Assessment and Forecast by Country, 2019-2029 13.4.1 Brazil 13.4.2 Mexico 13.4.3 Argentina 13.4.4 Rest of Latin America 14. Europe America Artificial Intelligence in Healthcare Market Revenue (US$ Mn), 2019-2029 14.1. Key Market Findings 14.2. Long Term ROI Segments 14.3. Revenue Opportunity Influencing Factors 14.4. Market Revenue (USD Mn) Assessment and Forecast by Country, 2019-2029 14.4.1 Germany 14.4.2 France 14.4.3 Spain 14.4.4 UK 14.4.5 Russia 14.4.6 Poland 14.4.7 Rest of Europe 15. Asia Pacific Artificial Intelligence in Healthcare Market Revenue (US$ Mn), 20192029 15.1. Key Market Findings 15.2. Long Term ROI Segments 15.3. Revenue Opportunity Influencing Factors 15.4. Market Revenue (USD Mn) Assessment and Forecast by Country, 2019-2029 15.4.1 Emerging Asia 15.4.1.1 China 15.4.1.2 India 15.4.1.3 ASEAN-5 15.4.1.4 Rest of Emerging Asia 15.4.2 Japan 16. Rest of World Artificial Intelligence in Healthcare Market Revenue (US$ Mn), 2019-2029 16.1. Key Market Findings 16.2. Long Term ROI Segments 16.3. Revenue Opportunity Influencing Factors 16.4. Market Revenue (USD Mn) Assessment and Forecast by Country, 2019-2029 16.4.1 Middle East 16.4.2 South Africa 16.4.3 North Africa 16.4.4 Rest of World 16.4.5 Others 17. Company Profiles 17.1. Competition Landscape 17.2. Global Company Share (USD Mn) Overview, 2019 17.3. Company Profiles 17.3.1 Nvidia 17.3.1.1 Corporate Overview 17.3.1.2 Financial Performance 17.3.1.3 Peer Comparison & 3C marketing equation 17.3.1.4 Company Strategy & Channel Management 17.3.2 Intel 17.3.2.1 Corporate Overview 17.3.2.2 Financial Performance 17.3.2.3 Peer Comparison & 3C marketing equation 17.3.2.4 Company Strategy & Channel Management 17.3.3 Google 17.3.3.1 Corporate Overview 17.3.3.2 Financial Performance 17.3.3.3 Peer Comparison & 3C marketing equation 17.3.3.4 Company Strategy & Channel Management 17.3.4 IBM 17.3.4.1 Corporate Overview 17.3.4.2 Financial Performance 17.3.4.3 Peer Comparison & 3C marketing equation 17.3.4.4 Company Strategy & Channel Management 17.3.5 Microsoft 17.3.5.1 Corporate Overview 17.3.5.2 Financial Performance 17.3.5.3 Peer Comparison & 3C marketing equation 17.3.5.4 Company Strategy & Channel Management 17.3.6 Medtronic 17.3.6.1 Corporate Overview 17.3.6.2 Financial Performance 17.3.6.3 Peer Comparison & 3C marketing equation 17.3.6.4 Company Strategy & Channel Management 17.3.7 General Electric 17.3.7.1 Corporate Overview 17.3.7.2 Financial Performance 17.3.7.3 Peer Comparison & 3C marketing equation 17.3.7.4 Company Strategy & Channel Management 17.3.8 Amazon Web Services 17.3.8.1 Corporate Overview 17.3.8.2 Financial Performance 17.3.8.3 Peer Comparison & 3C marketing equation 17.3.8.4 Company Strategy & Channel Management 17.3.9 Micron Technology 17.3.9.1 Corporate Overview 17.3.9.2 Financial Performance 17.3.9.3 Peer Comparison & 3C marketing equation 17.3.9.4 Company Strategy & Channel Management 17.3.10 Pillo 17.3.10.1 Corporate Overview 17.3.10.2 Financial Performance 17.3.10.3 Peer Comparison & 3C marketing equation 17.3.10.4 Company Strategy & Channel Management 17.3.11 17.3.11.1 17.3.11.2 17.3.11.3 17.3.11.4 17.3.12 17.3.12.1 17.3.12.2 17.3.12.3 17.3.12.4 17.3.13 17.3.13.1 17.3.13.2 17.3.13.3 17.3.13.4 17.3.14 17.3.14.1 17.3.14.2 17.3.14.3 17.3.14.4 17.3.15 17.3.15.1 17.3.15.2 17.3.15.3 17.3.15.4 17.3.16 17.3.16.1 17.3.16.2 17.3.16.3 17.3.16.4 17.3.17 17.3.17.1 17.3.17.2 17.3.17.3 17.3.17.4 17.3.18 17.3.18.1 17.3.18.2 17.3.18.3 17.3.18.4 17.3.19 17.3.19.1 17.3.19.2 Catalia Health Corporate Overview Financial Performance Peer Comparison & 3C marketing equation Company Strategy & Channel Management Ginger.Io Corporate Overview Financial Performance Peer Comparison & 3C marketing equation Company Strategy & Channel Management BioBeats Corporate Overview Financial Performance Peer Comparison & 3C marketing equation Company Strategy & Channel Management Icarbonx Corporate Overview Financial Performance Peer Comparison & 3C marketing equation Company Strategy & Channel Management Qventus Corporate Overview Financial Performance Peer Comparison & 3C marketing equation Company Strategy & Channel Management Caresyntax Corporate Overview Financial Performance Peer Comparison & 3C marketing equation Company Strategy & Channel Management Gauss Surgical Corporate Overview Financial Performance Peer Comparison & 3C marketing equation Company Strategy & Channel Management Perceive3d Corporate Overview Financial Performance Peer Comparison & 3C marketing equation Company Strategy & Channel Management Next IT (A Verint Systems Company) Corporate Overview Financial Performance 17.3.19.3 Peer Comparison & 3C marketing equation 17.3.19.4 Company Strategy & Channel Management 17.3.20 Atomwise 17.3.20.1 Corporate Overview 17.3.20.2 Financial Performance 17.3.20.3 Peer Comparison & 3C marketing equation 17.3.20.4 Company Strategy & Channel Management 18. 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Global Artificial Intelligence in Healthcare Market is estimated to value over USD 37 billion by 2029 end and is expected to register a CAGR of over 50% during the forecast period 2019 to 2029. The artificial intelligence (AI) is capable of improving patient outcomes by accurately identifying the source cause of the disease, this is positively influencing the market growth.
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