Health Care Language Models and Their Fine-Tuning for Information Extraction: Scoping Review.

ABSTRACT:

Background

In response to the intricate language, specialized terminology outside everyday life, and the frequent presence of abbreviations and acronyms inherent in health care text data, domain adaptation techniques have emerged as crucial to transformer-based models. This refinement in the knowledge of the language models (LMs) allows for a better understanding of the medical textual data, which results in an improvement in medical downstream tasks, such as information extraction (IE). We have identified a gap in the literature regarding health care LMs. Therefore, this study presents a scoping literature review investigating domain adaptation methods for transformers in health care, differentiating between English and non-English languages, focusing on Portuguese. Most specifica

SUBMITTER: Nunes M 

PROVIDER: S-EPMC11535799 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature