🩺 Diabetes Prediction System using SVM

📌 Project Overview

The Diabetes Prediction System is a Machine Learning based web application that predicts whether a person is diabetic or not using health-related parameters.

This project uses the Support Vector Machine (SVM) algorithm and provides predictions through an interactive Flask web application.

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🚀 Features

• Diabetes Risk Prediction
• Machine Learning Model using SVM
• Interactive Flask Web Interface
• Responsive User Interface
• Real-Time Prediction
• Professional Healthcare Dashboard Design

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🧠 Machine Learning Algorithm

• Support Vector Machine (SVM)

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📊 Dataset

Dataset Used:

• Pima Indians Diabetes Dataset

Input Parameters:

1. Pregnancies
2. Glucose
3. Blood Pressure
4. Skin Thickness
5. Insulin
6. BMI
7. Diabetes Pedigree Function
8. Age

Output:

• Diabetic
• Not Diabetic

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🎯 Model Accuracy

Accuracy Achieved:

76%

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🛠️ Tech Stack

• Python
• Flask
• HTML
• CSS
• JavaScript
• Scikit-Learn
• NumPy
• Pandas

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📂 Project Structure

Diabetes-Prediction-System

├── dataset/

├── static/

├── templates/

├── app.py

├── train.py

├── svm_model.pkl

├── requirements.txt

└── README.md

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▶️ Installation

Clone Repository

git clone https://github.com/your-username/Diabetes-Prediction-System.git

Install Dependencies

pip install -r requirements.txt

Run Application

python app.py

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📸 Screenshots

• Prediction Result (Diabetic)
• Prediction Result (Not Diabetic)

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👨‍💻 Developer

Mauli Phad

Machine Learning & AI Enthusiast

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⭐ Future Improvements

• Heart Disease Prediction
• Multi-Disease Prediction System
• Cloud Deployment
• Improved Model Accuracy
• User Authentication