While ML models are powerful tools for predicting diabetes, their lack of interpretability presents a major challenge for clinical adoption. Healthcare professionals require AI models to not only be ...

To develop a machine learning (ML) algorithm to predict survival probabilities for patients with epithelial ovarian cancer (EOC).Data were obtained from the SEER database for women diagnosed with EOC ...

After combing through 4,000 existing medications, an artificial intelligence tool helped uncover one that saved the life of a patient with idiopathic multicentric Castleman's disease (iMCD).

Proteins are the workhorses that keep our cells running, and there are many thousands of types of proteins in our cells, each performing a specialized function. Researchers have long known that the ...

Should you grab your umbrella before you walk out the door? Checking the weather forecast beforehand will only be helpful if that forecast is accurate.

One of the promising applications of machine learning is in precision medicine, where disease risk is predicted using patient genetic data. However, creating an accurate prediction model based on ...

Large language models (LLMs) are poised to have a disruptive impact on health care. Numerous studies have demonstrated ...

The superior performance of the machine learning model compared to assessment by ... risk of ESKD to demonstrate the feasibility of using ML in a clinical setting to improve upon clinical prediction ...

Brian T. Feeley, MD, FAAOS, was bestowed with the 2025 Kappa Delta Elizabeth Winston Lanier Award for his research in advancing the understanding of muscle degeneration in rotator cuff injuries and ...