American Institute of Physics

Predicting stroke recovery motor progress using EEG data

A machine learning model trained on EEG data from patients recovering from strokes helps predict how new patients will regain ...
Visual Studio Magazine

Linear Regression with Pseudo-Inverse Training Using JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
Journal of Medical Internet Research

Passive Sensing for Mental Health Monitoring Using Machine Learning With Wearables and Smartphones: Scoping Review

Passive sensing via wearable devices and smartphones, combined with machine learning (ML), enables objective, continuous, and noninvasive mental health monitoring. Objective: This study aimed to ...
ahajournals.org

Part 7: Adult Basic Life Support: 2025 American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care

The American Heart Association’s 2025 Adult Basic Life Support Guidelines build upon prior versions with updated recommendations for assessment and management of persons with cardiac arrest, as well ...
IEEE

Enhanced Bayesian Optimized Support Vector Machine (BO-SVM) Classification and Prediction of Heart Disease

Abstract: Medical data analysis is increasingly used to plan, improve research techniques, and explain diagnoses. The allocation of medical resources is based on the prevalence of specific pathologies ...
IEEE

Design of a Generic Fault Diagnosis Model for Electrical Distribution Networks Using a Support Vector Machine (SVM) Algorithm

Abstract: This article presents the design and implementation of a generic model for fault diagnosis in electrical distribution networks, based on the Support Vector Machine (SVM) algorithm. The ...