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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM38983
Volume:
8 |
11 |
Nov 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
This research paper presents the development of a medical chatbot utilizing cutting-edge technologies, specifically the Langchain framework and the Llama 2 language model, in conjunction with the PineCone database for efficient data storage and retrieval. The primary objective of this project is to create an intelligent conversational agent capable of providing reliable medical information, assisting users in symptom assessment, and guiding them towards appropriate healthcare resources. The integration of Langchain facilitates seamless interaction between the user interface and the underlying LLM, enabling natural language understanding and generation. Leveraging the advanced capabilities of the Llama 2 model ensures that the chatbot can engage in meaningful dialogues while maintaining context and relevance. Additionally, PineCone serves as a robust solution for managing and indexing medical data, enhancing the chatbot’s ability to deliver accurate and context-aware responses. This study explores the design, implementation, and potential implications of our medical chatbot, contributing to the emerging field of AI-driven healthcare solutions and underscoring its role in improving patient engagement and access to medical advice.
KEYWORDS
Publication Date
11/21/2024
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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