This project presents a neural network-based classifier to predict whether a person is at risk of developing chronic kidney disease (CKD).

This project aims to predict Chronic Kidney Disease (CKD) using machine learning techniques. The prediction is based on the "Chronic_kidney" dataset.

This project focuses on the early prediction of Chronic Kidney Disease (CKD) using various machine learning algorithms and feature selection techniques. Leveraging the CKD dataset from the UCI Machine Learning Repository, the goal is to assist healthcare professionals by providing a reliable tool for timely diagnosis.

Chronic kidney disease (CKD) is a long-term disorder which causes the kidneys to not function as well as they should.Our goal is to predict whether a subject has the chance of getting chronic kidney disease from a given set of data using machine learning.

I delve into the realm of medical prediction using machine learning techniques applied to a dataset containing various clinical features associated with CKD

This project aims to predict chronic kidney disease (CKD) using patient data and machine learning techniques. It focuses on early detection and prediction of CKD based on clinical features and lab test results.

This project focuses on predicting Chronic Kidney Disease (CKD) using machine learning techniques. The system analyzes patient medical data to classify whether a person is likely to have CKD or not. Multiple machine learning models are implemented and compared to achieve better prediction accuracy.

A capstone project focused on developing a Chronic Kidney Disease (CKD) prediction system using Machine Learning classifiers integrated with Explainable AI (XAI) techniques to enhance model transparency, interpretability, and clinical decision support.

# Chronic Kidney Disease Prediction This project applies machine learning techniques to predict the presence of Chronic Kidney Disease (CKD) using patient health data. Built with Python and libraries such as Scikit-learn, Pandas, and Matplotlib, the model leverages various classification algorithms to identify CKD risk and support early diagnosis.

To develop a reliable and accurate CKD prediction model using Machine Learning techniques. This model will assist healthcare professionals in identifying high-risk individuals at an early stage, enabling them to provide more effective care and intervention.

This project focuses on the early detection and prediction of Chronic Renal Disease (CRD), also known as Chronic Kidney Disease (CKD), using machine learning techniques. The objective is to assist healthcare professionals in diagnosing CRD in its early stages to prevent severe complications and improve patient outcomes.