The study aimed to predict the risks of Major adverse cardiac events (MACE) in patients undergoing peritoneal dialysis (PD) with machine learning (ML) algorithm. In addition, we added the time factor ...

The deep learning revolution has a curious blind spot: the spreadsheet. While Large Language Models (LLMs) have mastered the nuances of human prose and image generators have conquered the digital ...

The deep learning revolution has a curious blind spot: the spreadsheet. While Large Language Models (LLMs) have mastered the nuances of human prose and image generators have conquered the digital ...

Diabetes is a chronic condition that affects a substantial portion of the global population and is linked to elevated mortality rates and a range of severe health complications. Despite its clinical ...

WEDNESDAY, Nov. 6, 2024 (HealthDay News) -- Clinical data and machine learning can help to predict intradialytic hypotension (IDH) for patients undergoing hemodialysis, according to a study published ...

This study investigates the transformative potential of big data analytics in healthcare, focusing on its application for forecasting patient outcomes and enhancing clinical decision-making. The ...

The risk prediction model for kidney failure and death in people with chronic kidney disease (CKD) presented in the linked study is a super learner. A super learner is an algorithm that repeatedly ...

Objectives To compare the prediction effects of six models based on machine learning theories, which can provide a methodological reference for predicting the risk of type 2 diabetes mellitus (T2DM).

Laboratory of Data Science and Digital Inclusion, Institut de Mathématiques et de Sciences Physiques, Université d’Abomey-Calavi, Abomey-Calavi, Bénin. Diabetes is a chronic disease. In 2019, it was ...

Ambulatory blood pressure monitoring (ABPM) is routinely performed in children with chronic kidney disease to identify masked hypertension, a risk factor for accelerated chronic kidney disease ...