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

The disease is known for its strong association with climatic variables, especially excessive rainfall, high humidity, and ...

Background Current risk scores inadequately predict long-term mortality after transcatheter aortic valve replacement (TAVR), ...

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

A global study shows machine learning improves survival predictions for hospitalised cirrhosis patients, outperforming ...

We spoke with endocrinologists to explore the potential of artificial intelligence in the management of chronic disease, including diabetes, obesity, and PCOS.

A machine learning model may help predict mortality for hospitalized patients with cirrhosis at the time of admission, according to research published in Gastroenterology.The model, which used Random ...

Artificial intelligence and machine learning are transforming acute respiratory distress syndrome (ARDS) management, enabling ...

A team of Mayo Clinic researchers has developed an artificial intelligence (AI) system that can detect surgical site ...

AI-trained data analysis models may offer a more rapid and accurate detection of a range of neurologic conditions, including ...

A new study published in Scientific Reports has introduced a promising diagnostic tool that could dramatically shorten the long wait times many families face when seeking evaluations for autism and ...