Objectives Predicting mortality is vital for tailoring treatments, improving care and reducing costs. Machine learning (ML) has shown strong potential, often outperforming traditional severity-of-illness scoring

Objectives Interoperability, the seamless exchange and use of data across digital health systems, is essential for integrated, efficient healthcare delivery. However, evidence on its adoption

Objectives Evaluate the technical integration and usability of an intraoperative predictive machine learning model for colorectal anastomotic leakage within the Epic electronic health records (EHRs)

Objectives Lung cancer is the leading cause of cancer-related mortality worldwide, with poor prognosis largely due to late-stage diagnosis. Current screening methods such as low-dose

Objectives Hybrid hospital-at-home (HaH) models, combining remote patient monitoring (RPM) with home visits, offer an alternative to inpatient care. Yet, evidence on how RPM is

The deployment of artificial intelligence (AI) translation tools in healthcare is accelerating rapidly, yet regulatory frameworks lag dangerously behind clinical practice. Recent data reveal that