HealthWise: AI-Powered Medical Chatbot with Llama 2

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 – Medical Chatbot, Langchain, Llama-2, Pine Cone, Natural Language Processing, Artificial Intelligence, Machine Learning, Generative Artificial Intelligence.

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Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2024-11-27
DOI
https://doi.org/10.55041/ijsrem38983
Citations
1
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.35
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article

HealthWise: AI-Powered Medical Chatbot with Llama 2

Rashmi Phalnikar, Angshuman Nag, Rajeev Bansal, Aditya Krishna Vangipurapu et al.
1 citations
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
AI in Service Interactions
0.35
article

HealthWise: AI-Powered Medical Chatbot with Llama 2

Rashmi Phalnikar, Angshuman Nag, Rajeev Bansal, Aditya Krishna Vangipurapu, Swarup Shivaji Satav
article en
1 citations

Abstract

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 – Medical Chatbot, Langchain, Llama-2, Pine Cone, Natural Language Processing, Artificial Intelligence, Machine Learning, Generative Artificial Intelligence.

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 08(11)
MIT World Peace University (IN)
Quality Education
Openalex Percentile: Top 31%
AI in Service Interactions
0.35
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