Beyond Self-Consistency: Ensemble Reasoning Boosts Consistency and Accuracy of LLMs in Cancer Staging

arXiv:2404.13149v1 Announce Type: new
Abstract: Advances in large language models (LLMs) have encouraged their adoption in the healthcare domain where vital clinical information is often contained in unstructured notes. Cancer staging status is available in clinical reports, but it requires natural language processing to extract the status from the unstructured text. With the advance in clinical-oriented LLMs, it is promising to extract such status without extensive efforts in training the algorithms. Prompting approaches of the pre-trained LLMs that elicit a …

abstract accuracy adoption advances arxiv beyond cancer clinical cs.ai cs.cl domain ensemble extract healthcare information language language models language processing large language large language models llms natural natural language natural language processing notes processing reasoning reports staging type unstructured vital