MedEase : An AI Driven Medical Chatbot Using LLMs, Lang chain and Vector Searching for Scalable Healthcare Assistance

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Autores principales: Ashutosh Verma, Aryan, Sandeep Kumar Yadav
Formato: Recurso digital
Publicado: Zenodo 2026
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author Ashutosh Verma
Aryan
Sandeep Kumar Yadav
author_facet Ashutosh Verma
Aryan
Sandeep Kumar Yadav
contents This research presents MedEase, an AI-powered medical chatbot designed to provide accurate, context-aware health guidance to users. The system integrates large language models (LLMs) with LangChain to manage conversational flow and maintain contextual understanding. To retrieve relevant medical information efficiently, Pinecone is employed for vector-based semantic search. A Flask web interface enables real-time user interaction, while AWS ensures scalable hosting, secure data management, and high availability. The chatbot has been evaluated on curated medical queries, demonstrating its ability to deliver reliable, understandable, and personalized responses. This work highlights how combining LLMs, vector databases, web frameworks, and cloud infrastructure can produce a practical and intelligent healthcare assistant, bridging gaps in accessible medical information.
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_19554786
institution Zenodo
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publishDate 2026
publisher Zenodo
record_format zenodo
spellingShingle MedEase : An AI Driven Medical Chatbot Using LLMs, Lang chain and Vector Searching for Scalable Healthcare Assistance
Ashutosh Verma
Aryan
Sandeep Kumar Yadav
AI-powered medical chatbot
large language models
LangChain
vector search
Pinecone
Flask
cloud infrastructure
This research presents MedEase, an AI-powered medical chatbot designed to provide accurate, context-aware health guidance to users. The system integrates large language models (LLMs) with LangChain to manage conversational flow and maintain contextual understanding. To retrieve relevant medical information efficiently, Pinecone is employed for vector-based semantic search. A Flask web interface enables real-time user interaction, while AWS ensures scalable hosting, secure data management, and high availability. The chatbot has been evaluated on curated medical queries, demonstrating its ability to deliver reliable, understandable, and personalized responses. This work highlights how combining LLMs, vector databases, web frameworks, and cloud infrastructure can produce a practical and intelligent healthcare assistant, bridging gaps in accessible medical information.
title MedEase : An AI Driven Medical Chatbot Using LLMs, Lang chain and Vector Searching for Scalable Healthcare Assistance
topic AI-powered medical chatbot
large language models
LangChain
vector search
Pinecone
Flask
cloud infrastructure
url https://doi.org/10.5281/zenodo.19554786