About MediMind
MediMind is a medical symptom analyzer designed to provide users with informative insights based on their self-reported symptoms. It combines the speed and efficiency of a pre-trained recurrent neural network (RNN) with the contextual understanding of a large language model (LLM) to offer a more comprehensive symptom analysis.
Key Goals:
To empower users with a better understanding of their health concerns.
To provide initial insights that might assist users in making informed decisions about seeking medical care.
Important Disclaimer: MediMind is intended for informational purposes only and should never replace professional medical advice. Always consult with a qualified healthcare provider for diagnosis and treatment.
Benefits & Capabilities
Speed and Efficiency: The pre-trained RNN provides a rapid initial assessment, allowing for quick insights.
Enhanced Accuracy: Combining RNN and LLM models improves the accuracy and reliability of the analysis.
Contextual Understanding: The LLM considers the entire conversation history, including initial symptoms and follow-up answers, for better context.
Actionable Recommendations: Treatment and prevention suggestions are provided to help users take appropriate action.
User-Friendly Interface: The intuitive Streamlit interface makes the system easy to use.
Future Enhancements
Enhanced RAG Pipeline: Implement a robust RAG system for efficient retrieval of medical knowledge from a vector database.
Recursive Web Scraping: Integrate web scraping to continuously update the knowledge base with current medical information.
Advanced Query Parsing: Improve query understanding using NER and dependency parsing for more accurate information retrieval.
Contextual Conversation: Enhance conversational memory to maintain context across multiple turns for improved dialogue flow.
External API Integration: Integrate with relevant medical APIs (e.g., drug databases) to expand the chatbot’s knowledge.