Both approaches identified hemoglobin as one of the most significant predictors of CKD risk. Additional top-ranked features included blood urea, sodium levels, red blood cell count, potassium, and ...

Priya Hays, Hays Documentation Specialists, LLC, discusses biomarker discovery through artificial intelligence and ...

Zimmer said SynTuition matched expert’s PJI diagnosis 96% of the time, outperforming pooled physicians who matched experts 91% of the time.

The adoption of machine learning approaches in systematic reviews is fundamentally transforming evidence-based medicine. Traditionally, systematic reviews have involved painstaking manual screening of ...

A multi-institutional research team has demonstrated how artificial intelligence and machine learning can optimize therapy selection and dosing for septic shock, a life-threatening complication that ...

Metabolite data and AI combine to redefine how we measure aging and predict health spans. Study: Metabolomic age (MileAge) predicts health and life span: A comparison of multiple machine learning ...

A powerful artificial intelligence (AI) tool could give clinicians a head start in identifying life-threatening complications ...

Current models of mortality risk after heart failure (HF) rely primarily on cardiac-specific clinical variables and may ...

A mother's health during pregnancy, childbirth and the postpartum period is the foundation of lifelong well-being, directly influencing a child's development and long-term outcomes, yet most ...

From wearables for health monitoring and self-care apps, to machine learning analysis of medical images, the potential of digital technologies to revolutionise healthcare has commanded many headlines.