Hanadi Ghalib, Nazar Mahmood
Understanding Healthy Eating Habits of Elderly People in a Geriatric Center in Kirkuk City: A Cross-Sectional Study
Cureus
data categorization top concern medical data predict detect illnesses thus applied modern healthcare informatics modern informatics machine learning deep learning models enjoyed great attention categorizing medical data improving illness detection however existing techniques features high dimensionality computational complexity longterm execution duration raise fundamental problems study presents novel classification model employing metaheuristic methods maximize efficient positives chronic kidney disease diagnosis medical data initially massively preprocessed data purified various mechanisms including missing values resolution data transformation employment normalization procedures focus processes leverage handling missing values prepare data deep analysis adopt binary grey wolf optimization method reliable subset selection feature using metaheuristics operation aimed improving illness prediction accuracy classification step model adopts extreme learning machine hidden nodes data optimization predict presence ckd complete classifier evaluation employs established measures including recall specificity kappa fscore accuracy addition feature selection data related study show proposed approach records high levels accuracy better existing models