AI model forecasts ICU vital signs and flags kidney injury earlier
The study's architectural choices reflect a broader shift in how machine learning researchers approach clinical time-series data. The Temporal Fusion ...
The study's architectural choices reflect a broader shift in how machine learning researchers approach clinical time-series data. The Temporal Fusion ...
The distinction between discrimination and calibration deserves particular attention when interpreting the reported performance figures. Discrimination, captured by the AUROC, ...
A two-step machine learning framework trained on more than 23,000 clinical records from Indian newborn units identified 84.9 percent of ...
A two-stage machine learning framework can predict health insurance claim denials before submission and assign likely reason codes, achieving a ...
A machine learning analysis of over ten million English adults shows the top one percent of patients by cost account ...
A real-world study of 9000 patients with type 2 diabetes in China used cluster analysis to identify three clinical phenotypes ...
A multicenter Chinese study shows an interpretable random forest model using nine routine clinical variables can strongly discriminate mild cognitive ...
Researchers argue that the deepest ethical risks of AI in long-term care lie not in algorithms but in the systems, ...
Researchers used hierarchical agglomerative clustering to sort the Veterans Health Administration's eighteen regions into four interpretable profiles that align with ...
Researchers at Fayoum University show that a simple averaged ensemble of machine learning models, evaluated on the OhioT1DM dataset with ...
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© 2025 Scienmag - Science Magazine