Researchers at the University at Albany and Rutgers University have developed an early-warning framework that can predict harmful social media interactions before they erupt, paving the way for ...
Background Preprocedural risk prediction of 30-day all-cause mortality after percutaneous coronary intervention (PCI) aids in clinical decision-making and benchmarking hospital performance. This study ...
Type 1 diabetes (T1D) is an autoimmune condition in which the body's own immune system attacks insulin-producing cells. As a ...
In high-stakes settings like medical diagnostics, users often want to know what led a computer vision model to make a certain prediction, so they can determine whether to trust its output. Concept ...
Abstract: Diabetes affects 537 million people worldwide, making it the deadliest and most frequent noncommunicable disease. According to studies on diabetes patients, the prevalence of diabetes in ...
Incorporating marble dust and polypropylene fibers in concrete boosts strength and durability, highlighting the role of machine learning in mix optimization.
A new machine learning model built using a simple and interpretable approach predicts in-hospital death in patients with acute liver failure and reveals top risk drivers.
Machine learning predicts who will decline faster in Alzheimer’s disease using routine clinic data
Researchers developed and validated ElasticNet machine learning models that predict 12-month MMSE and BADL outcomes in ...
However, inconsistent travel times and unpredictable congestion continue to undermine service reliability, particularly in ...
More than half of transplant recipients in a large analysis developed chronic graft-versus-host disease, and 15% died from causes other than cancer relapse. Those numbers capture the uneasy truth of ...
Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...
A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
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