Long-term VBC success hinges on robust data integrity and seamless integration across clinical, claims, government and personal health data sources.

The rapid integration of digital technologies and mobile health (mHealth) has fundamentally transformed the landscape of ...

You might be surprised by some of the jobs you can do from home.

Risk prediction has been used in the primary prevention of cardiovascular disease for >3 decades. Contemporary cardiovascular risk assessment relies on multivariable models, which integrate ...

A new international study suggests most clinical artificial intelligence (AI) tools are not yet ready for safe, equitable use ...

An interactive workshop at HIMSS26 offers healthcare leaders hands-on advice for integrating LLMs into clinical workflows – and engineering them for cost-effectiveness and speed.

Practice management services firm ApolloMD says 626,000 patients of affiliated physicians and practices were impacted by a ...

During his early 40s, Geisler was diagnosed with multiple sclerosis, a diagnosis that gave him a deeper insight into the problems caused by fragmented data-sharing platforms.

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...

An AI framework developed by Nashville, Tenn.-based Vanderbilt University identified statin intolerance, contraindications and patient deferrals documented in clinical notes for 10% of adult patients.

Drawing on his leadership roles within the SiLA Consortium and ASTM’s The Analytical Information Markup Language (AnIML), Schaefer explains why open standards and lightweight metadata are essential to ...