IEEE

Performance Analysis of Diabetes Disease Prediction Using Machine Learning Classification Algorithms

Abstract: Diabetes is a medical disorder disease that affects our body's food fuel systems. Eating food is converted to glucose and discharged to different body parts through blood and the pancreas ...
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, ...

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 ...