Project Overview:

The Health Data Insights & Prediction Portal is a web-based analytics platform that helps users, hospitals, and health organizations to analyze health datasets and make data-driven predictions about various diseases or health trends using machine learning models. Users can upload datasets (e.g., patient records, disease stats), visualize insights, and receive predictive analytics such as diabetes risk, heart disease probability, or epidemic spread forecasts.

The system combines data science, AI/ML, and web development technologies to turn raw health data into actionable knowledge.

Core Features:

1. Upload Health Datasets (CSV/Excel)

2. Automatic Data Analysis & Cleaning

3. Predictive Analytics (e.g., Diabetes, Heart Disease)

4. Data Visualizations (Pie, Bar, Heatmaps)

5. Explore Trends by Age, Gender, Location, etc.

6. Save & Compare Multiple Datasets

7. Role-Based Access: Admin / Doctor / Public User

Technology Stack:

Backend (choose one):

• PHP + MySQL

• Node.js + MongoDB

• Java Spring Boot + PostgreSQL

Frontend:

• HTML5 + CSS3 + Bootstrap

• JavaScript (AJAX, Chart.js, DataTables.js)

AI/ML Engine (Python):

• Libraries: Pandas, Scikit-learn, XGBoost, TensorFlow

• Model Types: Logistic Regression, Random Forest, Decision Trees

• Hosted as Flask or FastAPI microservice

How It Works (Workflow):

1. Data Input:

   • User uploads dataset (CSV/Excel)

   • Backend parses, validates, and stores it

2. Data Insights:

   • Summary stats: number of patients, disease counts

   • Charts: gender vs disease, age vs condition, etc.

   • Interactive filters for slicing data

3. ML-Based Prediction:

   • Choose from models: Diabetes, Heart Disease, Stroke Risk

   • Input parameters (age, BP, sugar, cholesterol)

   • Model returns: prediction + probability score

4. Visualization Dashboard:

   • Live charts: Pie, Bar, Area, Heatmap

   • Disease trends across time, demographics, location