AI Model Classifies Arrhythmia Risk in Three Clinical Levels
A new deep learning algorithm called PaliConvLSTM classifies arrhythmias into three risk levels, achieving 99.68% accuracy on standard ECG datasets ...
A new deep learning algorithm called PaliConvLSTM classifies arrhythmias into three risk levels, achieving 99.68% accuracy on standard ECG datasets ...
A comprehensive review published in Food Production, Processing and Nutrition synthesizes the current applications of artificial intelligence in food risk ...
A drug-target Mendelian randomization study found that genetically elevated osteoprotegerin levels are associated with a reduced risk of type 2 ...
Researchers have developed an integrated management framework that combines the Impact Chain Tool and Bow-Tie Analysis to support adaptation planning ...
A multicenter retrospective study validated an admission-based prediction model estimating the risk of two- to eight-week coronary artery Z score ...
A fine-tuned random forest model categorized global disaster events into impact classes using spatiotemporal and contextual data available at initial ...
A new systematic review protocol aims to evaluate the performance of Leicester risk scores for detecting undiagnosed type 2 diabetes ...
A multicenter cross-sectional study of 300 hospital nurses in Chongqing evaluated a nomogram-based risk model that identifies prevalent occupational musculoskeletal ...
A novel variational autoencoder framework named MyeVAE integrates clinical traits and multi-modal genomic data to enhance survival risk prediction in ...
A new study reveals that federated learning for EEG data remains vulnerable to privacy attacks, though differential privacy can significantly ...
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© 2026 Scienmag - Science Magazine