Generated with AI

DOCTOR-AI README

Overview

DOCTOR-AI is a medical assistant web application built using Streamlit that helps individuals and doctors with diagnostic assistance. The platform allows patients to input their symptoms and medical history to receive a preliminary diagnosis and prescription suggestions, while doctors can use the tool to get differential diagnoses based on patient data. The application is designed to help users by providing a base level of medical insight, but it is essential to consult a healthcare professional for accurate and reliable medical advice.

Features

• Patient Mode: Patients can input personal information, symptoms, medical history, and current medications. The system will analyze the data and provide a preliminary diagnosis with suggested medications.
• Doctor Mode: Doctors can input patient data and upload medical reports to receive differential diagnoses and additional suggestions for treatment or next steps.
• Chat Interface: An interactive chat interface powered by AI allows users to ask medical questions, receive responses, and get diagnostic insights based on the input data.
• File Upload: Doctors can upload medical reports (PDFs, images, Word documents) for further analysis, which enhances diagnosis suggestions.
• Medical Disclaimer: All AI-generated advice comes with a disclaimer that it should not replace professional medical consultation.

Try it Here

https://doctor-ai-by-avijit.streamlit.app/

Prerequisites

Before running the application, ensure the following requirements are met:

• Python 3.x
• Streamlit
• pandas
• io
• External helper functions (located in utils.py)

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/doctor-ai.git
   cd doctor-ai

2. Install dependencies: Install the required libraries by running:

   pip install -r requirements.txt

3. Run the Streamlit app: After the installation is complete, you can run the app using Streamlit:

   streamlit run app.py

Application Workflow

1. Patient Mode

• Step 1: Upon starting the app, patients are prompted to fill in their personal and medical information, including:
  • Name, Age, Gender, Height, Weight, Blood Group
  • Symptoms, Medical History, Current Medications, Extra Details
• Step 2: Once the form is filled, patients can submit the data, which is analyzed by the AI assistant to provide a preliminary diagnosis.
• Step 3: The patient can interact with the AI assistant via the chat interface to clarify symptoms and receive additional information.
• Step 4: The AI provides a diagnosis based on the input data and the conversation.

2. Doctor Mode

• Step 1: Doctors can input patient information similar to patients but with a broader focus, including the ability to upload medical reports for a more in-depth diagnosis.
• Step 2: Doctors will receive a differential diagnosis based on the patient's data, which helps in understanding possible conditions and treatment recommendations.
• Step 3: The platform analyzes uploaded files (e.g., PDFs, images, etc.) and incorporates them into the diagnosis process.
• Step 4: The doctor receives the diagnosis result, which may include suggestions for further investigation.

3. Interactive Chat

• The chat interface allows for continuous interaction between the user (patient or doctor) and the AI assistant, making the diagnostic process more dynamic.
• The chat history is maintained, so users can refer to earlier exchanges during the consultation.

Code Structure

The app consists of the following key components:

• app.py: Main Streamlit app containing all the page logic, patient and doctor mode handling, and UI elements.
• utils.py: Helper functions for processing patient data, generating diagnoses, and interacting with the medical AI model.
• requirements.txt: Python dependencies for the project (Streamlit, pandas, etc.).
• assets/: Folder containing any images or other static resources for the app.

UI/UX Design

• The app uses Streamlit's simple but powerful UI components, including text inputs, buttons, text areas, and file uploaders.
• The design is minimalistic but functional, with a clear separation between the patient and doctor modes.
• Custom CSS is used to enhance the appearance of the interface, making it more user-friendly and visually appealing.

Known Issues and Limitations

• Accuracy: The AI-generated diagnoses are based on a simple set of rules and are not a substitute for professional medical evaluation.
• File Upload Limitations: Depending on the file size, there may be limits on the types and sizes of reports that can be uploaded.
• Performance: The performance of the app may be affected by the complexity of the input data and the AI's response time.

Future Enhancements

• Advanced AI Models: The system can be integrated with more advanced machine learning models for better diagnostic accuracy.
• Database Integration: Storing user and patient data for analysis and improving AI responses.
• Mobile Compatibility: Optimizing the app for mobile use for broader accessibility.
• Real-time Consultations: Adding video and audio capabilities for real-time doctor-patient consultations.

License

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

Disclaimer

Disclaimer: The AI assistant provided by DOCTOR-AI is for educational and informational purposes only. The generated diagnoses should not be used as a substitute for professional medical advice, diagnosis, or treatment. Always seek the advice of your physician or another qualified health provider with any questions you may have regarding a medical condition.