Abstract: In this research, we present the revolutionary ‘EffiDenseGenOp’ framework for Polycystic Ovary Syndrome (PCOS) detection, leveraging the amalgamation of Ensembled Transfer Learning Models.

As predictive medicine advances, legal scholars warn that decades-old federal guidelines could set up a potential clash between your genes and your job.

Depression is a highly common mental health condition that affects millions of people worldwide. Medical professionals have ...

Scientists in China used computer analyses to identify two genes driving pulmonary arterial hypertension that may prove a therapeutic target.

AI is transforming medicine by improving diagnostics, personalized treatments, and operational efficiency. Key opportunities include AI-powered drug discovery, precision medicine, wearables for ...

Predicting observable traits from genetic variation remains difficult due to the complex interplay of multiple genes and environmental influences. Widely used statistical approaches are limited in ...

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle collisions at the LHC. This new approach can reconstruct collisions more quickly ...

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 ...