May 13, 2024, 4:41 a.m. | Fatemeh Nazary, Yashar Deldjoo, Tommaso Di Noia, Eugenio di Sciascio

cs.LG updates on

arXiv:2405.06270v1 Announce Type: new
Abstract: The integration of Large Language Models (LLMs) into healthcare diagnostics offers a promising avenue for clinical decision-making. This study outlines the development of a novel method for zero-shot/few-shot in-context learning (ICL) by integrating medical domain knowledge using a multi-layered structured prompt. We also explore the efficacy of two communication styles between the user and LLMs: the Numerical Conversational (NC) style, which processes data incrementally, and the Natural Language Single-Turn (NL-ST) style, which employs long narrative …

abstract arxiv clinical context context learning cs.lg decision development diagnostics domain domain knowledge few-shot healthcare in-context learning integration knowledge language language models large language large language models llms machine machine learning machine learning models making medical novel outlines prompt study type zero-shot

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