Summary of Two-layer Retrieval-augmented Generation Framework For Low-resource Medical Question Answering Using Reddit Data: Proof-of-concept Study, by Sudeshna Das et al.

Two-Layer Retrieval-Augmented Generation Framework for Low-Resource Medical Question Answering Using Reddit Data: Proof-of-Concept Study

by Sudeshna Das, Yao Ge, Yuting Guo, Swati Rajwal, JaMor Hairston, Jeanne Powell, Drew Walker, Snigdha Peddireddy, Sahithi Lakamana, Selen Bozkurt, Matthew Reyna, Reza Sameni, Yunyu Xiao, Sangmi Kim, Rasheeta Chandler, Natalie Hernandez, Danielle Mowery, Rachel Wightman, Jennifer Love, Anthony Spadaro, Jeanmarie Perrone, Abeed Sarker

First submitted to arxiv on: 29 May 2024

GrooveSquid.com Paper Summaries

GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!

Summary difficulty	Written by	Summary
High	Paper authors	High Difficulty Summary Read the original abstract here
Medium	GrooveSquid.com (original content)	Medium Difficulty Summary The paper proposes a retrieval-augmented generation (RAG) architecture for medical question answering, utilizing user-generated social media data to provide insights on emerging issues associated with health-related topics. A two-layer RAG framework is designed for query-focused answer generation, which generates individual summaries followed by an aggregated summary to efficiently answer medical queries from large amounts of user-generated data. The performance of the quantized large language model (Nous-Hermes-2-7B-DPO) is compared with GPT-4 in a proof-of-concept study, using Reddit data to answer clinicians’ questions on xylazine and ketamine use. The framework achieves comparable median scores across various evaluation metrics, demonstrating its effectiveness in answering medical queries about targeted topics.
Low	GrooveSquid.com (original content)	Low Difficulty Summary The paper develops a new way for computers to understand and answer complex medical questions by combining different types of information from social media platforms like Reddit. This system can help doctors quickly get answers to important questions about new drugs or treatments. The researchers tested their approach using data from Reddit and found that it worked just as well as other, more powerful systems.