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.

In high-stakes settings like medical diagnostics, users often want to know what led a computer vision model to make a certain prediction, so they can determine whether to trust its output. Concept ...

Domain adaptation may be a novel creative solution to predict infection risk in patients with chronic lymphocytic leukemia ...

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 ...

Researchers at Fondazione Policlinico Universitario Agostino Gemelli IRCCS have developed a promising machine learning algorithm capable of predicting survival and cause of death for patients with ...

Abstract: Infant mortality is a public health concern that serves as a key indicator of the overall well-being of a population. This research employs machine learning models to predict infant ...

Abstract: Employee attrition is a costly problem for organizations, leading to loss of institutional knowledge, reduced productivity, and increased recruitment expenses. Machine learning offers a ...

What was once experimental research is now becoming operational backbone across modern energy systems. In the editorial ...

A machine learning model for prediction of preeclampsia risk using routinely collected data was feasible among pregnancies in ...

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

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

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, ...