Pathog-PDx, a machine learning system, diagnoses pediatric respiratory infections within hours of admission—significantly faster than conventional testing and reducing unnecessary antibiotics.

Recent Geriatrics & Aging coverage reveals convergence: aging is measurable across independent modalities—radiographic structure, neural function, microbial ecology. Biomarkers predict mortality and disease before symptoms appear, enabling early…

Early detection transforms fire response. This wireless deep-ultraviolet sensor system detects flames at ignition, before smoke appears.

Artificial intelligence can detect muscle loss (sarcopenia) in pediatric brain tumor patients using routine clinical MRI scans, identifying cases that traditional weight measurements miss.

BRIDGE predicts pathological complete response to neoadjuvant breast cancer therapy by analyzing intratumoral molecular subtype composition, outperforming existing clinical predictors.

A fully automated platform rapidly analyzes stroke lesions and predicts long-term cognitive outcomes, potentially transforming personalized acute stroke prognostication.

Standard 24-hour pH tests miss some clinically significant reflux cases. A machine learning framework identifies potential false negatives by analyzing subtle waveform patterns conventional metrics overlook.

An interpretable AI model predicts blood clot risk after endometrial cancer surgery with 82% accuracy, making machine learning decisions transparent to clinicians.

An expert-derived algorithm accurately classifies surgical complications from administrative billing codes, outperforming machine learning and enabling cost-effective, real-time quality surveillance.

New research demonstrates that large language models cannot reliably perform causal reasoning about HIV treatment, drug interactions, and side effects—raising serious safety concerns.