Simulations and experiments meet: Machine learning predicts gold nanocluster structures

Researchers at University of Jyväskylä (Finland) advance understanding of gold nanocluster behavior at elevated temperatures ...
IEEE

Machine Learning Techniques to Improve the Cognitive Workload Classification Using Multimodal Sensors’ Data

Abstract: Using machine learning applied to multimodal physiological data allows the classification of cognitive workload (low, moderate, or high load) during task performance. However, current ...
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 ...
IEEE

Anomaly Detection in ECG Signal Using Unsupervised Learning

Abstract: An essential diagnostic tool for finding irregularities in the rhythm and function of the heart is the electrocardiogram (ECG) signal. After obtaining the ECG signals from the adjacent ...
Frontiers

Reinforcement Learning-Guided Optimization of ECG Features for Enhanced Heart Disease Prediction using Stacked CNNs

The final, formatted version of the article will be published soon. Accurate and timely heart disease diagnosis through intelligent ECG signal processing is essential to reducing death rates and ...
Frontiers

End-to-End Non-Invasive ECG Signal Generation from PPG Signal: A Self-Supervised Learning Approach

The final, formatted version of the article will be published soon. Electrocardiogram (ECG) signals are frequently utilized for detecting important cardiac events, such as variations in ECG intervals, ...