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

There is unprecedented opportunity to use machine learning to integrate high-dimensional
molecular data with clinical characteristics to accurately diagnose and manage disease …

Medical real-world data stored in clinical systems represents a valuable knowledge source
for medical research, but its usage is still challenged by various technical and cultural …

Background Thorough data stewardship is a key enabler of comprehensive health research.
Processes such as data collection, storage, access, sharing, and analytics require …

A concise and measurable set of FAIR (Findable, Accessible, Interoperable and Reusable)
principles for scientific data is transforming the state-of-practice for data management and …

Introduction Chronic Pelvic Pain (CPP) is a complex, multifaceted condition that affects both
women and men. There is limited literature on the cost utilization the healthcare system and …

Objective This paper introduces a privacy-preserving federated machine learning (ML)
architecture built upon Findable, Accessible, Interoperable, and Reusable (FAIR) health …

Background Sharing health data is challenging because of several technical, ethical, and
regulatory issues. The Findable, Accessible, Interoperable, and Reusable (FAIR) guiding …

Computational models are often employed in systems biology to study the dynamic
behaviours of complex systems. With the rise in the number of computational models, finding …

Background Secondary use of routine medical data is key to large-scale clinical and health
services research. In a maximum care hospital, the volume of data generated exceeds the …