Abstract: The CKD will becoming a serious health problem around the world, mostly because it is often diagnosed too late &many people do not have access to early prediction tools. This project was started to beg help to raise toast about kidney health &to use modern technology, like machine learning, to help solve this issue. The goal was to build a system that can predict the chances of a person having CKD &also give them advice on how to live a healthier life to manage or reduce the risk. During the project, we used real patient data that included results from medical tests &other health information. A Gradient Boosting Classifier, which will be a mechanism learning model, was trained using this information to make smart &accurate predictions. The system also gives easy-to-understand & lifestyle tips like changes in diet, exercise, &medicine based on each person’s health. This helps people take care of their kidneys before serious problems start.
Keywords: Chronic Kidney Disease Gradient Boosting Random Forest Logistic Regression, Flask Application, Prediction System, Healthcare Technology, Lifestyle Recommendation, Medical Diagnosis.
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DOI:
10.17148/IJIREEICE.2025.13902
[1] TANUJA S M, Mr. PRASHANT ANKALKOTI, "Machine Learning Models for Chronic Kidney Disease Detection," International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering (IJIREEICE), DOI 10.17148/IJIREEICE.2025.13902