Researchers conducted a systematic review to assess the risk of bias and applicability of prediction models for fear of recurrence in patients with cancer.

Researchers have unveiled an interpretable, lightweight AI text detection framework using classical machine learning models that achieves near-perfect accuracy while lowering computational costs.

Artificial intelligence (AI) is emerging as a powerful tool to predict food consumption patterns and guide policy decisions, ...

A predictive model for psoriasis relapse risk demonstrates moderate performance, according to a study published online April ...

Using routinely collected baseline data across 11 registries, prediction of remission showed limited discrimination and was best suited to ruling out remission. Performance was similar for a ...

New research reveals a model to predict chronic immune thrombocytopenia in children at diagnosis. Learn how it could guide ...

Why This MattersChildren undergoing thoracic surgery face unique challenges, especially when one-lung ventilation (OLV) is ...

A pain-informed model identified risk factors for clinically significant nausea in patients undergoing metabolic bariatric surgery.

Background Native aortic valve endocarditis continues to present significant operative challenges, often complicated by heart ...

The study, titled “GenAI-Powered Framework for Reliable Sentiment Labeling in Drug Safety Monitoring,” published in Applied ...

New research using AI-powered stacked ensemble models has improved accuracy in predicting NBA game results by combining multiple machine learning algorithms. These models not only forecast outcomes ...