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.

Debate continues over the role of artificial intelligence in treating mental health conditions, but new research shows that machine learning models can help predict whether a person might benefit from ...

Researchers developed and validated ElasticNet machine learning models that predict 12-month MMSE and BADL outcomes in ...

AI in genomics offers transformative opportunities by enhancing drug discovery and personalized medicine through efficient genomic data analysis. Drivers include the surge in genomic data, the focus ...

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

How people with compromised immune systems respond to vaccines is an important area of immunological research. A study led by York University has found that not only could machine-learning models ...

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 ...

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

Machine-learning models accurately pinpointed differences in immune responses in healthy controls and those living with HIV.

Given the success of the Digital Medicine and Chronic Neurological Disorders, we are pleased to announce Volume II.Digital medicine is the clinical part of ...

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.