Advances for Artificial Intelligence in Health Data Analytics to Drive Digital Systems Innovation

Opportunities and Challenges in Digital Healthcare Innovation - Advances in Medical Technologies and Clinical Practice ◽

10.4018/978-1-7998-3274-4.ch001 ◽

2020 ◽

pp. 1-12

Author(s):

Kamaljeet Sandhu

Keyword(s):

Artificial Intelligence ◽

Health Services ◽

Data Analytics ◽

Health Data ◽

Modern Technology ◽

Digital Systems ◽

Clear Understanding ◽

Vested Interests ◽

The Government ◽

Health Data Analytics

Artificial intelligence in health (AIH) and health data has become a focus of attention for customers of health services, organizations providing health services, and the government organization monitoring the performance and outcome for health services. These three groups have vested interests in how, where, and when the health data can be used and delivered to facilitate and streamline the delivery and process for health services from adopting AIH. The driving force in AIH for health data analytics stems from the discovery of new information, analysis that seeks to provide a clear understanding of a problem, interpretation in making clear sense of the problem, and communication of meaningful data patterns that can be effectively used in finding solutions to drive digital systems innovation. Modern technology provides an important platform for the health data transformation at different stages of the process to deliver different kinds of health services adopting artificial intelligence.

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Intelligent health data analytics: A convergence of artificial intelligence and big data

Healthcare Management Forum ◽

10.1177/0840470419846134 ◽

2019 ◽

Vol 32 (4) ◽

pp. 178-182 ◽

Cited By ~ 11

Author(s):

Syed Sibte Raza Abidi ◽

Samina Raza Abidi

Keyword(s):

Artificial Intelligence ◽

Big Data ◽

Health Outcomes ◽

Health System ◽

Data Analytics ◽

Heterogeneous Data ◽

Health Data ◽

Care Quality ◽

System Management ◽

Health Data Analytics

Healthcare is a living system that generates a significant volume of heterogeneous data. As healthcare systems are pivoting to value-based systems, intelligent and interactive analysis of health data is gaining significance for health system management, especially for resource optimization whilst improving care quality and health outcomes. Health data analytics is being influenced by new concepts and intelligent methods emanating from artificial intelligence and big data. In this article, we contextualize health data and health data analytics in terms of the emerging trends of artificial intelligence and big data. We examine the nature of health data using the big data criterion to understand “how big” is health data. Next, we explain the working of artificial intelligence–based data analytics methods and discuss “what insights” can be derived from a broad spectrum of health data analytics methods to improve health system management, health outcomes, knowledge discovery, and healthcare innovation.

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Deep Neural Artificial Intelligence for IoT Based Tele Health Data Analytics

Computers Materials & Continua ◽

10.32604/cmc.2022.019041 ◽

2022 ◽

Vol 70 (3) ◽

pp. 4467-4483

Author(s):

Nithya Rekha Sivakumar ◽

Ahmed Zohair Ibrahim

Keyword(s):

Artificial Intelligence ◽

Data Analytics ◽

Health Data ◽

Health Data Analytics

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Digital Systems Innovation for Health Data Analytics

Advances in Healthcare Information Systems and Administration - Handbook of Research on Optimizing Healthcare Management Techniques ◽

10.4018/978-1-7998-1371-2.ch019 ◽

2020 ◽

pp. 261-270 ◽

Cited By ~ 3

Author(s):

Kamaljeet Sandhu

Keyword(s):

Health Information ◽

Data Analytics ◽

Service Providers ◽

Digital Health ◽

Health Data ◽

Digital Systems ◽

Easy Access ◽

Health Innovation ◽

Care Health ◽

Health Data Analytics

Digital innovation for health data analytics has faced obstacles in systems implementation and consumer acceptance. Research suggests that digital health innovation has been a challenge and a slow process for acceptance. At the same time it offers tremendous opportunities in health data analytics for consumers of health services and service providers, such as health information portability, personalization of health information by consumers, easy access and usefulness of health information, better management of data records by institutions and government, and management of information by healthcare staff for patients' engagement and care. Health data analytics is the key for driving digital systems for health innovation. This research seeks to identify the digital health innovation opportunities and obstacles, develop a framework and a conceptual model for digital health innovation that empowers consumer of digital health to use the information to make informed decisions and choices.

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