Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
Irrespective of their personal, professional and social circumstances, different individuals can experience varying levels of life satisfaction, fulfillment and happiness. This general measure of life ...
Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...
A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...
In a recent study published in the eBioMedicine, a group of researchers predicted depressive symptom severity (DSS) (intensity or degree of depressive symptoms an individual is experiencing) using ...
Machine learning and statistical prediction of overall survival (OS) from pre-dose plasma biomarkers in a randomized phase 2 trial (1801 Part 3B) of the GSK-3 inhibitor elraglusib in metastatic ...
Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.
The Opioid Risk Tool for Opioid Use Disorder may help identify patients with chronic noncancer pain at increased risk for OUD ...
Interpretable AI model could offer new insights into why medicines cause certain side effects, helping to improve future drug safety predictions.
Forecasting inflation has become a major challenge for central banks since 2020, due to supply chain disruptions and economic uncertainty post-pandemic. Machine learning models can improve forecasting ...
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