IEEE

Heart Disease Prediction Using a Hybrid Feature Selection and Ensemble Learning Approach

Abstract: Heart diseases have become the leading cause of death globally, highlighting the urgent need for robust diagnostic and treatment methods. This study leverages the UCI heart disease dataset ...
IEEE

A Critical Analysis on Evolution of Feature Selection Strategies in Machine Learning Models

Abstract: Data accomplishes astonishing sensation; however, the data's massiveness and distinctive features are obstacles to acquiring promising results. Feature selection (FS) algorithms can develop ...
The Santa Fe New Mexican

Demons' loss leaves fate in selection committee's hands

Get the latest local and state news, updates, and exclusive content with a $10 digital trial month. See how our content fits ...
The Manila Times

Lotto Champ 2026: AI Marketing Claims, Pricing, Refund Terms, and What Consumers Should Verify Before Buying

Informational 2026 overview of the LottoChamp AI lottery number tool - examining algorithm claims, data-driven ...

Passify Releases New Quantitative Report on Multi-Algorithm Correlation and Risk Aggregation

A technical study from Passify examining how unintended strategy correlation increases portfolio risk and the necessity ...
The American Journal of Managed Care

Machine Learning May Enable Earlier Detection of CKD Risk Factors

Both approaches identified hemoglobin as one of the most significant predictors of CKD risk. Additional top-ranked features included blood urea, sodium levels, red blood cell count, potassium, and ...
Scientific Research Publishing

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ()

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...