🏥 ML-Based Health Chatbot

Overview

The ML-Based Health Chatbot is a project that leverages machine learning and natural language processing (NLP) to provide users with health-related information and assistance. The chatbot can answer common health questions, provide information on symptoms, suggest possible treatments, and more.

✨ Features

• 🤖 Conversational interface for health-related inquiries.
• 🏥 Provides information on symptoms and possible treatments.
• 📊 Uses NLP to understand and respond to user queries.
• 🌐 Web-based interface for easy access.

🚀 Getting Started

Prerequisites

• 🐍 Python 3.7 or higher
• 🤗 Transformers (Hugging Face)
• 🧠 TensorFlow 2.x or PyTorch
• 🧮 NumPy
• 🐼 Pandas
• 📊 Matplotlib
• 🌐 Flask (for the web interface)
• 💬 NLTK or SpaCy (for NLP preprocessing)

📥 Installation

1. Clone the repository:

   git clone https://github.com/your-username/health-chatbot.git
   cd health-chatbot

2. Install the required packages:

   pip install -r requirements.txt

📚 Dataset

For training, you can use publicly available health-related datasets such as the COVID-19 Open Research Dataset (CORD-19).

🏋️‍♂️ Training the Model

1. Preprocess the data:

   python preprocess_data.py --dataset_path path/to/health/dataset --output_path path/to/save/preprocessed/data

2. Train the chatbot model:

   python train_model.py --data_path path/to/preprocessed/data --output_model_path path/to/save/model

💬 Using the Chatbot

To interact with the chatbot:

1. Run the chatbot server:

   python app.py

   Open your browser and go to http://127.0.0.1:5000 to start chatting with the bot.

📂 Project Structure

• preprocess_data.py: Script to preprocess the health dataset.
• train_model.py: Script to train the chatbot model.
• app.py: Flask application for the web interface.
• model.py: Contains the model architecture and related functions.
• utils.py: Utility functions for data processing and model operations.
• requirements.txt: List of required packages.

📑 References

• CORD-19 Dataset
• Transformers Documentation
• Flask Documentation

📜 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgements

• The Hugging Face team for their excellent Transformers library.
• The creators of the CORD-19 dataset for providing a valuable resource for training health-related models.