Chronic Disease Prediction using Machine Learning

📌 Project Overview

This project focuses on predicting chronic kidney disease (CKD) using machine learning techniques. The goal is to assist in early detection by analyzing patient medical data and identifying patterns associated with chronic disease risk.

🎯 Objectives

• Perform data preprocessing and cleaning
• Handle missing values and categorical variables
• Train and evaluate machine learning models
• Predict chronic kidney disease

🗂️ Dataset

• Kidney Disease Dataset (CSV)
• Target Variable: CKD (Yes / No)
• kaggle data set : https://www.kaggle.com/datasets/mansoordaku/ckdisease/

🛠️ Technologies Used

• Python
• Jupyter Notebook
• NumPy
• Pandas
• Scikit-learn
• Matplotlib
• Seaborn

⚙️ Workflow

• Data Loading
• Exploratory Data Analysis
• Data Preprocessing
• Model Training
• Model Evaluation
• Prediction

🚀 How to Run

bash
pip install numpy pandas scikit-learn matplotlib seaborn
jupyter notebook

Run Chronic disease prediction.ipynb

📊 Evaluation

• Accuracy Score
• Confusion Matrix
• Classification Report

👨‍💻 Author

Mohamed Ansari

📄 License

Educational Use Only