Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...

"Medical Genomics" research group at ISTA "Data Science, Machine Learning, and Information Theory" research group at ISTA Al ...

To prevent algorithmic bias, the authors call for multivariable modeling frameworks that jointly incorporate biological sex, genetic ancestry, and gender-related life-course exposures.

Fragments of DNA from long-extinct human relatives still circulate in modern genomes, and in some cases they do more than ...

Machine learning is helping neuroscientists organize vast quantities of cells’ genetic data in the latest neurobiological cartography effort.

Abstract: This research focuses on the solution of optimization problem, through the construction of INS-GA model, the genetic algorithm is used to optimize the data combination, and the elite ...

This project implements an advanced Virtual Machine Placement (VMP) optimization system that leverages multi-objective genetic algorithms, machine learning predictions, blockchain technology, and ...

This study integrated scRNA-seq and bulk RNA-seq data to identify macrophage subpopulations in degenerative tissues and constructed co-expression modules using hdWGCNA. Functional enrichment was ...

This project focuses on detecting cyber attacks using machine learning techniques. It employs various algorithms to analyze network traffic and identify potential threats in real-time.

The workflow encompasses patient datacollection and screening, univariate regression analysis for initial variable selection, systematic comparison of 91 machine learning models,selection and ...

A machine learning algorithm used gene expression profiles of patients with gout to predict flares. The PyTorch neural network performed best, with an area under the curve of 65%. The PyTorch model ...