Chronic kidney disease prediction based on machine learning

Abstract

Chronic kidney disease (CKD) is a serious and potentially lifelong condition, often caused by factors like kidney malfunctions or reduced kidney function. Early detection and appropriate treatment are crucial for slowing down or halting its progression, preventing the need for life- preserving interventions like dialysis or surgeryIn a supervised learning setting, we've evaluated twelve different machine learning classifiers. The XgBoost classifier has emerged as the top performer, boasting an accuracy of 0.983, precision of 0.98, recall of 0.98, and an F1-score of 0.98.Our research underscores the potential of recent advances in machine learning and predictive modeling for discovering innovative solutions, not only for kidney disease but also for broader applications in healthcare and beyond.