The boundaries between clinical care, data science, and tech are fast dissolving, making way for a new blueprint for ...

Clinical data management is entering a new phase as AI automates EDC build, shortens timelines, and enables data teams to focus on quality.

Data access empowerment operating models enable public health leaders to make timely, informed decisions with trusted intelligence and faster insights.

At the HIMSS26 AI in Healthcare Forum, MGB's chief information and digital officer described strategies for governance, safety and sustainability as it strives to integrate artificial intelligence ...

Discover the impact of digital pathology on drug discovery and biomarker research this International Women’s Day with Dr ...

Sex-specific data is redefining Lifestyle Medicine – and why University of South Carolina School of Medicine Greenville is building the model ...

Health systems move beyond the pilot era over health systems to integrate AI into workflows with governance for safe, compliant adoption.

The current kidney care model—focused on late-stage disease and in-center hemodialysis—is unsustainable, because of costs, environmental burden, poor outcomes, and reduced quality of life.

Objective Geriatric patients often face issues related to polypharmacy and adverse drug events. Re-evaluating prescribed medications and considering deprescribing is critical. Medication discrepancies ...

In The Lancet Digital Health, a systematic review and meta-analysis by Alabed Samer and colleagues1 provides a clear picture about the current state of clinical artificial intelligence (AI) in ...

Researchers from the Johns Hopkins Kimmel Cancer Center and The Johns Hopkins University have created a novel database structure that allows investigators anywhere to more easily study multiple types ...

Electronic health records (EHRs); insurance claims; patient registries; wearable tech: Never before has health data been so abundant. However, the United States continues to struggle with siloed ...