Medical Literature Mining and Retrieval in a Conversational Setting

• URL: http://arxiv.org/abs/2108.01436v1
• Date: Fri, 23 Jul 2021 23:02:59 GMT
• Title: Medical Literature Mining and Retrieval in a Conversational Setting
• Authors: Souvik Das, Sougata Saha, and Rohini K. Srihari
• Abstract summary: Covid-19 pandemic has caused a spur in the medical research literature. There is a need for robust text mining tools which can process, extract and present answers from the literature in a concise and consumable way. We present a conversational system, which can retrieve and answer coronavirus-related queries from the rich medical literature, and present it in a conversational setting with the user.
• Score: 3.37411253119822
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The Covid-19 pandemic has caused a spur in the medical research literature. With new research advances in understanding the virus, there is a need for robust text mining tools which can process, extract and present answers from the literature in a concise and consumable way. With a DialoGPT based multi-turn conversation generation module, and BM-25 \& neural embeddings based ensemble information retrieval module, in this paper we present a conversational system, which can retrieve and answer coronavirus-related queries from the rich medical literature, and present it in a conversational setting with the user. We further perform experiments to compare neural embedding-based document retrieval and the traditional BM25 retrieval algorithm and report the results.

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