A machine learning model may help predict mortality for hospitalized patients with cirrhosis at the time of admission, ...

For inpatients with cirrhosis, a machine learning (ML) model using random forest (RF) analysis is superior for prediction of ...

Let’s say there are 100 records in the training dataset. The observations are arranged in decreasing order of probability ...

Longer treatment duration, not having diabetes, and using semaglutide are among the factors linked to better weight reduction over 12 months.

Early intervention in psoriatic arthritis (PsA) is disease-modifying, and delays in diagnosis, even by 6 months, can reduce ...

Post-cerclage cervical length offers a better predictive value for spontaneous preterm birth than pre-cerclage cervical ...

Sai Krishna's work in text mining has earned him well-deserved recognition within his organization. His development of an RShiny-based machine learning workbench was a game-changer, leading to ...

Predicting who might die while in the hospital is one of the hardest challenges for doctors caring for people with serious liver disease.

Researchers have found in a new study that both Clostridioides difficile infection (CDI)-hospitalized patients with end-stage ...

Wealthier markets and hospital capacity were key drivers of robotic radical cystectomy adoption, independent of local ...

Rapid molecular testing with FilmArray Pneumonia Panel offers high diagnostic accuracy but shows limited value in predicting ...

In a study published in Alzheimer's & Dementia, a team led by Dr. Sha Feng from the Shenzhen Institute of Advanced Technology of the Chinese Academy of Sciences—collaborating with Dr. Jed A. Barash ...