A machine learning model based on electronic health record data can provide updated predictions of preeclampsia risk, ...

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.

Discover how AI healthcare technology and machine learning diagnosis are transforming disease detection, improving accuracy, and reshaping patient care in today's evolving medical landscape.

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

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 ...

WPI researchers use machine learning and brain scans to identify age- and sex-specific anatomical patterns that predict ...

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 ...

Drug discovery is like molecular Tetris. Chemists snap atoms together, adjusting the pieces until everything fits and suddenly, a molecule makes a promising new medicine. Normally, creating better ...

What’s the first thing you think of when you hear about ai security threats and vulnerabilities? If you’re like most people, your mind probably jumps to Large Language Model (LLM) ...

Machine learning is a multibillion-dollar business with seemingly endless potential, but it poses some risks. Here's how to avoid the most common machine learning mistakes. Machine learning technology ...