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.

A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a complication that can occur late in pregnancy. Preeclampsia is a sudden ...

LCGC International’s interview series on the evolving role of artificial intelligence (AI)/machine learning (ML) in separation science continues with Boudewijn Hollebrands from Unilever Foods R&D, ...

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

A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a complication that can occur late in pregnancy. Preeclampsia is a sudden ...

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

A new computational method allows modern atomic models to learn from experimental thermodynamic data, according to a ...

Artificial intelligence tools are increasingly being developed to predict cancer biology directly from microscope images, ...

University of Warwick research warns that popular deep learning systems trained for cancer pathology may be relying on hidden ...

This research initiative highlights the importance of ethical and explainable artificial intelligence in workforce ...

A research team funded by the National Institutes of Health (NIH) has developed a versatile machine learning model that could one day greatly expand ...

Scientists develop a forecasting system that predicts high-risk windows and regions for solar superflares, using 50 years of X-ray data and machine learning techniques.