A machine learning model bests traditional methods for predicting cirrhosis mortality among hospitalized patients.

Researchers at Pennsylvania State University examined whether machine learning could predict the risk and contributing ...

Findings from a new study published in Annals of Family Medicine show that a machine learning model accurately predicts ...

A new study presents a machine learning model that accurately predicts the compressive strength of high-strength concrete, offering a more reliable and efficient alternative to traditional estimation ...

Machine learning models showed strong predictive performance for 5-year survival in stage III colorectal cancer patients, with AUC values between 0.766 and 0.791. Key prognostic factors identified ...

New method using Raman spectroscopy and machine learning estimates organic maturity in rocks, crucial for oil exploration, ...

A machine learning model developed to predict 5-year survival in stage III colorectal cancer patients highlights key ...

Researchers have found a way to make the chip design and manufacturing process much easier — by tapping into a hybrid blend ...

Supervised learning is a machine learning approach in which algorithms are trained on labelled datasets—that is, data that already includes the correct outputs or classifications. The model learns to ...

For inpatients with cirrhosis, a machine learning (ML) model using random forest (RF) analysis is superior for prediction of inpatient mortality, according to a study published online July 23 in ...