Summary of Explainable Biomedical Hypothesis Generation Via Retrieval Augmented Generation Enabled Large Language Models, by Alexander R. Pelletier et al.
Explainable Biomedical Hypothesis Generation via Retrieval Augmented Generation enabled Large Language Models
by Alexander R. Pelletier, Joseph Ramirez, Irsyad Adam, Simha Sankar, Yu Yan, Ding Wang, Dylan Steinecke, Wei Wang, Peipei Ping
First submitted to arxiv on: 17 Jul 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| 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 presents RUGGED, a comprehensive workflow designed to support investigators with knowledge integration and hypothesis generation in biomedical research. It leverages Large Language Models (LLMs) to navigate complex data landscapes while minimizing hallucinatory responses through Retrieval Augmented Generation (RAG). The authors demonstrate the effectiveness of RUGGED in evaluating therapeutics for Arrhythmogenic Cardiomyopathy (ACM) and Dilated Cardiomyopathy (DCM), analyzing prescribed drugs for molecular interactions and unexplored uses. The platform integrates biomedical information from publications and knowledge bases, text-mining association analysis, and explainable graph prediction models to forecast potential links among drugs and diseases. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper is about a new tool that helps scientists understand lots of medical information. It uses special computers called Large Language Models (LLMs) to find important facts in a big haystack of data. But sometimes these LLMs can get things wrong, so the authors created a way to correct this using something called Retrieval Augmented Generation (RAG). This new tool is called RUGGED and it helps scientists make sense of lots of information and even suggests new treatments for diseases like heart problems. |
Keywords
» Artificial intelligence » Rag » Retrieval augmented generation
