Can deep learning catch chronic illness before symptoms show? This article explores how time-aware neural networks are reshaping early detection and care planning for conditions like diabetes and COPD ...
University of Virginia School of Data Science researcher Heman Shakeri has been awarded a major new research grant to lead work at the intersection of machine learning and diabetes care.
Researchers develop an AI tool to predict cardiometabolic multimorbidity risk in type 2 diabetes, aiding early intervention and personalised care. Find out more.
Nuclear fuel performance is critically dependent on understanding the evolution of fuel properties under operational conditions, a complex challenge driven by chemical changes and substantial ...
Abstract: Diabetes is a chronic condition affecting millions of people globally, requiring early and accurate prediction to mitigate associated health risks. This study employed a Kaggle dataset with ...
Abstract: This study evaluated three machine learning algorithms in predicting a diabetes mellitus diagnosis using a publicly available health data set. The models developed and analyzed in this study ...
Objective: Analyze the psychological and clinical factors of clinically significant tinnitus (THI score ≥38) in patients with hearing loss, construct predictive models based on four machine learning ...
Introduction: All angioedema (AE) presents with transient, localized swelling; however, the underlying causes, prognosis, and treatments vary significantly. Consequently, identifying a specific AE ...
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