Open Heart

Bridging machine learning and clinical practice: a multicentre nomogram for 90-day graft failure risk stratification in heart transplantation

Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...
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 ...
IEEE

Machine Learning for Parkinson’s Disease Detection: Analyzing Hybrid Voice Data With Spectral, Topological, and Random Matrix Methods

Abstract: Parkinson’s disease (PD) is a progressive neurodegenerative disorder that affects both motor and speech functions. Advances in machine learning and signal processing have enabled ...
IEEE

Matrix-Inversion-Free Sparse Bayesian Learning for High-Resolution Radar Imagery via Improved Variational Inference

Abstract: Sparse Bayesian learning (SBL) is an advanced statistical framework that dominantly enhances the sparse features of targets of interest in radar imagery. A widely adopted strategy for ...
Frontiers

Lobe-wise Cognitive Load Detection using Empirical Fourier Decomposition and Optimized Machine learning

The final, formatted version of the article will be published soon. Neural activity is stimulated by cognitive load, which is crucial for comprehending how the brain reacts to stimuli or mental strain ...