https://github.com/sanu0711/healthcare-intelligence

Enhancing Patient Care through AI-Driven Disease Prediction
https://github.com/sanu0711/healthcare-intelligence

ai-health-assistant chatbot decision-tree-classifier disease-prediction djang generative-ai k-nearest-neighbours leafletjs map medication-details medication-history naive-bayes-classifier py random-forest-classifier scikit-learn sklearn support-vector-machines symptom-checker voice-search

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Enhancing Patient Care through AI-Driven Disease Prediction

• Host: GitHub
• URL: https://github.com/sanu0711/healthcare-intelligence
• Owner: sanu0711
• Created: 2024-05-10T12:10:41.000Z (9 months ago)
• Default Branch: main
• Last Pushed: 2024-05-29T05:58:47.000Z (8 months ago)
• Last Synced: 2025-01-19T10:09:14.685Z (11 days ago)
• Topics: ai-health-assistant, chatbot, decision-tree-classifier, disease-prediction, djang, generative-ai, k-nearest-neighbours, leafletjs, map, medication-details, medication-history, naive-bayes-classifier, py, random-forest-classifier, scikit-learn, sklearn, support-vector-machines, symptom-checker, voice-search
• Language: Python
• Homepage:
• Size: 2.63 MB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Healthcare Intelligence 

Enhancing Patient Care through AI-Driven Disease Prediction

![GitHub last commit](https://img.shields.io/github/last-commit/sanu0711/Healthcare-Intelligence)

![GitHub repo size](https://img.shields.io/github/repo-size/sanu0711/Healthcare-Intelligence)

## Overview

The aim is to develop a comprehensive system that utilizes artificial intelligence (AI) and machine learning (ML) techniques to predict diseases based on user-provided symptoms and manage patient information effectively.

## Machine Learning Algorithms

The following machine learning algorithms were utilized for disease prediction:

- **Decision Tree:** Constructs a tree-like structure to make decisions based on feature values.

- **Random Forest:** Ensemble learning method that constructs multiple decision trees and outputs the mode of the classes.

- **Support Vector Machine (SVM):** Classifies data points by finding the hyperplane that best separates different classes.

- **K-Nearest Neighbors (KNN):** Classifies data points based on the majority class among their k nearest neighbors.

- **Naive Bayes:** Probabilistic classifier based on Bayes' theorem, assuming independence between features.

## Features

- **Disease Prediction:** Predict diseases based on user-provided symptoms.

- **Patient Report Generation:** Generate detailed patient reports including predicted disease, description, precautions, and medication suggestions.

- **Django Integration:** Implemented using Django framework, incorporating various features such as dynamic input chatbox, voice search, and location integration.

- **User-Friendly Interface:** Intuitive user interface with interactive features for seamless user experience.

- **AI Health Assistant (ChatBot) :** The AI Health Assistant provides tailored health guidance and information, harnessing cutting-edge AI models and advanced NLP techniques. Users can explore health tips, uncover causes, symptoms, and precautions, discover home remedies, receive medication guidance, and locate nearby hospitals.

## Video Demonstration

[![Watch the video](https://img.youtube.com/vi/6AW9Wzpxbzg/0.jpg)](https://www.youtube.com/watch?v=6AW9Wzpxbzg)

## Installation

1. Clone the repository:

    ```

    git clone https://github.com/sanu0711/Healthcare-Intelligence.git

    ```

2. Navigate to the project directory:

    ```

    cd DiseasePrediction

    ```

3. Install dependencies:

    ```

    pip install -r requirements.txt

    ```

## Contributors

- [Abhishek Yadav](https://github.com/sanu0711)