Abstract The National Academy of Medicine has long advocated for a “learning healthcare
system” that produces constantly updated reference data during the care process. Moving …

Abstract Objectives The HL7® fast healthcare interoperability resources (FHIR®)
specification has emerged as the leading interoperability standard for the exchange of …

Background Multicentre training could reduce biases in medical artificial intelligence (AI);
however, ethical, legal, and technical considerations can constrain the ability of hospitals to …

Heterogeneity is a problem in storing and exchanging data in a digital health information
system (HIS) following semantic and structural integrity. The existing literature shows …

Background: With the advent of the digital economy and the aging population, the demand
for diversified health care services and innovative care delivery models has been …

Background Health data analytics is an area that is facing rapid change due to the
acceleration of digitization of the health sector, and the changing landscape of health data …

In this article, we will discuss the genesis, evolution, and progress of the INternational Soft
Tissue SaRcoma ConsorTium (INSTRuCT), which aims to foster international research and …

The very first issue of the journal of Translational Behavioral Medicine (TBM) was dedicated,
in part, to the theme of Health Information Technology as a platform for evidence …

Integration of AI in healthcare requires an interoperable digital data ecosystem | Nature Medicine
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The trend of using and adopting E-Health is getting higher in the world. Moreover, with the
pandemic situation, which causes a need and compulsion by health service providers to be …