3 minute read

AI Healthcare Bot System using Python

September 8, 2024

1) Background/ Problem Statement

India faces a major challenge in providing affordable and high-quality healthcare services to its growing population, especially in rural areas where access to healthcare facilities is limited. This lack of access and the difficulty in obtaining transportation often leads patients to delay treatment or opt for closer, but less cost-efficient, medical options.

To address this issue, we have developed an AI Healthcare Bot system using Python. This system provides instant responses to patients’ health-related queries, helps them find doctors, clinics, and hospitals nearby, and offers a cost-efficient solution to accessing basic healthcare information.

2) Working of the System

The AI Healthcare Bot system comprises two modules: User and Admin.

User Module:
1. Registration & Login: Users must first register to access the system and log in with their credentials.
2. Profile Management: Users can update their profile and change their password if necessary.
3. Chat with the Bot: Users can interact with the AI bot to get answers to their health-related queries.
4. Find Healthcare Providers: Users can view nearby doctors, clinics, and hospitals using Google Places API.
Admin Module:
1. Login: Admins can log in with their credentials.
2. Manage Questions and Answers: Admins can add, update, and delete Q&A pairs in the chatbot’s dataset and retrain the model.
3. View Users: Admins can monitor registered users and their activities.

This system utilizes a custom-built dataset and employs a Convolutional Neural Network (CNN) for predicting general disease risk. The CNN algorithm provides higher accuracy compared to other methods.

Frontend: HTML, CSS, JavaScript
Backend: Python, Django Framework
Database: MySQL

3) Advantages

Provides real-time answers to users’ health-related queries.
Helps users find healthcare facilities (doctors, clinics, hospitals) near their location.
Highly efficient and saves time, especially in emergencies.
Offers a cost-effective solution for healthcare guidance.

4) System Description

User Features:
- Registration/Login: New users need to register; existing users can log in with their credentials.
- Profile Management: Update personal information and passwords.
- Chatbot Interaction: Get instant answers to health-related queries.
- Nearby Clinics/Doctors: Find healthcare providers using Google Places API.
- Nearby Hospitals: Search for nearby hospitals.
Admin Features:
- Login: Direct access to the system via credentials.
- Manage Questions/Answers: Add, update, or delete Q&A pairs and train the AI model.
- View Users: Access details of registered users.

5) Project Life Cycle

This project follows the Waterfall Model, a linear and sequential approach to system development. Each phase, such as requirement gathering, design, implementation, and testing, flows into the next without going back to previous steps, ensuring systematic development.

6) System Requirements

Hardware Requirements:
- PC or Laptop with Windows 7 or higher.
- Intel i3 processor or higher.
- 4GB RAM or higher.
- 100GB ROM or higher.
Software Requirements:
- Python (with required libraries).
- Sublime Text Editor or similar.
- XAMP Server for database management.

7) Limitations/Disadvantages

AI-based System: Limited human interaction, which can reduce personalized care.
Data Dependency: Incorrect data input can lead to inaccurate health advice or recommendations.

8) Application

Designed to assist users in resolving health-related queries and locating healthcare providers near their location.
Highly useful in rural or remote areas where healthcare access is limited.