A research paper by scientists from Beihang University proposed a machine learning (ML)-driven cerebral blood flow (CBF) prediction model, featuring multimodal imaging data integration and an ...
1 Department of Pediatrics, The First People’s Hospital of Nantong (Second Affiliated Hospital of Nantong University), Nantong, China 2 School of Nursing and Rehabilitation, Nantong University, ...
Advanced ECG feature extraction and SVM classification for predicting defibrillation success in OHCA
Out-of-hospital cardiac arrest (OHCA) represents a critical challenge for emergency medical services, with the necessity for rapid and accurate prediction of defibrillation outcomes to enhance patient ...
Abstract: The increase in mental health problems has prompted Machine Learning to approach efforts to accurately diagnose mental health. One technique that is frequently used in the classification ...
This important study introduces a fully differentiable variant of the Gillespie algorithm as an approximate stochastic simulation scheme for complex chemical reaction networks, allowing kinetic ...
Abstract: Using a machine learning algorithm for a given application often requires tuning design parameters of the classifier to obtain optimal classification performance without overfitting. In this ...
The algorithm development kit, based on Etiometry’s FDA-cleared clinical intelligence platform, is now available to support research and clinical decision making in high-acuity care units ...
Support Vector Machines (SVMs) are a powerful and versatile supervised machine learning algorithm primarily used for classification and regression tasks. They excel in high-dimensional spaces and are ...
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