Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...

Machine learning can predict many things, but can it predict who will develop schizophrenia years before the average ...

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 ...

Time series electrocardiography combined with AI predicted cardiac arrest with remarkable accuracy. Discover how this ...

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

Approximately one in seven adults in the United States has kidney disease, where the organs responsible for filtering waste ...

Approximately one in seven adults in the United States has kidney disease, where the organs responsible for filtering waste ...

India, Feb. 24 -- Why did the AI Impact Summit in Delhi draw so much attention in February 2026? Part of the answer is scale. The room held more than researchers and policy staff. It also brought in ...

AI integration in employer-sponsored health care is accelerating. Here are 5 key opportunities to drive better quality, ...

BACKGROUND: Forecasts for the future prevalence of cardiovascular disease and stroke are crucial to guide efforts to improve health outcomes across the life course for women. METHODS: Using historical ...

A new risk prediction model shows good predictive value in identifying risk for neurogenic bladder (NB) after spinal cord injury (SCI) and guiding clinical interventions, according to a study ...