Neveditsin Nikita, Lingras Pawan, Mago Vijay
Department of Mathematics and Computing Science, Saint Mary's University, Halifax, Nova Scotia, Canada.
School of Health Policy and Management, York University, Toronto, Ontario, Canada.
PLOS Digit Health. 2025 May 8;4(5):e0000800. doi: 10.1371/journal.pdig.0000800. eCollection 2025 May.
This paper explores the advancements and applications of language models in healthcare, focusing on their clinical use cases. It examines the evolution from early encoder-based systems requiring extensive fine-tuning to state-of-the-art large language and multimodal models capable of integrating text and visual data through in-context learning. The analysis emphasizes locally deployable models, which enhance data privacy and operational autonomy, and their applications in tasks such as text generation, classification, information extraction, and conversational systems. The paper also highlights a structured organization of tasks and a tiered ethical approach, providing a valuable resource for researchers and practitioners, while discussing key challenges related to ethics, evaluation, and implementation.
本文探讨了语言模型在医疗保健领域的进展与应用，重点关注其临床用例。它考察了从早期需要大量微调的基于编码器的系统到能够通过上下文学习整合文本和视觉数据的最先进的大语言和多模态模型的演变。分析强调了可本地部署的模型，这些模型增强了数据隐私和操作自主性，以及它们在文本生成、分类、信息提取和对话系统等任务中的应用。本文还强调了任务的结构化组织和分层的伦理方法，为研究人员和从业者提供了宝贵的资源，同时讨论了与伦理、评估和实施相关的关键挑战。
