Benchmarking clinical reasoning and accuracy of large language models on breast oncology multiple-choice questions.

Translating regenerative medicine from lab research to large-scale clinical and commercial production requires robust, scalable, and tightly controlled ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

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 ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...

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

DataZapp brings AI and machine learning to deliver affordable, predictive demand generation and marketing data for home ...

A recent eClinicalMedicine study utilized machine learning (ML) techniques to develop and test a predictive prognostic model (PPM) for early dementia prediction using real-world patient data. Study: ...