Recent Pathology coverage shows the field moving beyond benchmark accuracy: specialized models are entering workflow studies, while multimodal systems make tissue morphology more actionable for molecular and treatment…

Can one pretrained model support multiple decisions across the emergency department? In retrospective multicenter testing, ED-Foundation delivered leading performance across triage, outcome prediction, and treatment-phase decision-support tasks using…

Continuously collected, 1-second-resolution vital signs predicted impending circulatory and respiratory instability with good external discrimination. Converting machine-learned patterns into expert-refined rules improved alert-level performance while retaining clinical interpretability.

A Transformer-based AI-ECG model predicted incident atrial fibrillation (AF) several days before its detection and improved physicians’ risk assessment in simulated clinical cases. Its clearest contribution was better…

Consumer AI chatbots generally maintained pediatric-health safety boundaries in this benchmark, including when caregivers applied adversarial pressure. Yet the study also identifies specific conditions—especially false claims of medical…

Allergic rhinitis (AR) is commonly framed as an immune-mediated disease, but this single-cell multi-omics study places epithelial injury and stromal activation at the center of its nasal mucosal…

Korea’s regulatory clinical-investigation landscape has shifted sharply toward digital medical devices. Compared with traditional devices, digital products were more often evaluated in pivotal and retrospective investigations and, among…

When patient-level data cannot be pooled across hospitals, synthetic data may offer a route forward—but only if it remains statistically credible and useful for clinical modelling. In a…

UNITE shows that shallow, low-cost plasma cell-free DNA sequencing can support tumor-naive cancer detection when multiple fragmentomic and copy-number signals are integrated. The results are encouraging, but performance…

Integrating transcriptomic, proteomic, and DNA-methylation data improved prediction of treatment response in ovarian cancer in a matched TCGA-OV cohort. The OMICS-FUSE framework also linked its predictions to biologically…