A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a ...

A new machine learning model built using a simple and interpretable approach predicts in-hospital death in patients with acute liver failure and reveals top risk drivers.

More than a decade ago, researchers launched the BabySeq Project, a pilot program to return newborn genomic sequencing results to parents and measure the effects on newborn care. Today, over 30 ...

Precision medicine and multidisciplinary care in gastric and gastroesophageal junction (G/GEJ) cancers: Challenges and practice gaps in community cancer clinics. This is an ASCO Meeting Abstract from ...

Postpartum depression (PPD) affects up to 15 percent of individuals after childbirth. Early identification of patients at risk of PPD could improve proactive mental health support. Researchers ...

Thirty-day mortality of patients with major trauma fell if they received intubation before hospital admission per prediction from a machine learning risk-stratifying model, according to data published ...

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