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

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.

The final, formatted version of the article will be published soon. "Facial Beauty" is not an absolute physical attribute but a subjective social and cultural construct. Facial beauty assessment is an ...

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

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 ...

Proteogenomics explores how genetic information translates into protein expression and function, and the role of changes across DNA, RNA, and proteins in influencing disease development and ...

1 Key Laboratory of Evaluation and Utilization of Livestock and Poultry Resources (Sheep) of the Ministry of Agriculture and Rural Areas, Institute of Animal Sciences, Xinjiang Academy of Animal ...