Heart Disease Risk Prediction

Heart Disease Risk Prediction System

Backend system for managing patient data and predicting heart disease risk using a machine learning model.

Overview

This project is a backend-focused system built using Laravel, designed to handle patient records, appointments, and prediction requests through RESTful APIs.

Key Features RESTful API for patient and appointment management Machine Learning integration via Flask API JWT Authentication & Role-Based Access Control (RBAC) Redis caching for performance optimization MySQL database with normalized schema and constraints

Tech Stack Backend: PHP (Laravel) Database: MySQL Caching: Redis ML Service: Python (Flask) Tools: Postman, Git

System Architecture

The system follows a modular architecture:

Laravel backend handles API requests and business logic Flask service processes prediction requests Redis is used to optimize response time

Getting Started git clone https://github.com/haneen... cd heart-disease-backend composer install cp .env.example .env php artisan key:generate php artisan migrate php artisan serve

API Example

POST /api/predict

Request:

{ "age": 45, "cholesterol": 230 }

Response:

{ "risk": "High" }

Project Resources