Global Artificial Intelligence in Healthcare Market is Estimated to Value Over USD 37 Billion by 2029 End

  • 29 Jul 2019

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 real-world 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.

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

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


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