Girouard Michael P, Chang Alex J, Liang Yilin, Hamilton Steven A, Bhatt Ankeet S, Svetlichnaya Jana, Fitzpatrick Jesse K, Carey Evan C B, Avula Harshith R, Adatya Sirtaz, Lee Keane K, Solomon Matthew D, Parikh Rishi V, Go Alan S, Ambrosy Andrew P
Department of Cardiology, Kaiser Permanente San Francisco Medical Center, 2425 Geary Boulevard, San Francisco, CA, 94115, USA.
Department of Medicine, Kaiser Permanente San Francisco Medical Center, 2425 Geary Boulevard, San Francisco, CA, 94115, USA.
Heart Fail Rev. 2025 Mar;30(2):407-415. doi: 10.1007/s10741-024-10472-0. Epub 2024 Dec 19.
Natural language processing (NLP) is a burgeoning field of machine learning/artificial intelligence that focuses on the computational processing of human language. Researchers and clinicians are using NLP methods to advance the field of medicine in general and in heart failure (HF), in particular, by processing vast amounts of previously untapped semi-structured and unstructured textual data in electronic health records. NLP has several applications to clinical research, including dramatically improving processes for cohort assembly, disease phenotyping, and outcome ascertainment, among others. NLP also has the potential to improve direct clinical care through early detection, accurate diagnosis, and evidence-based management of patients with HF. In this state-of-the-art review, we present a general overview of NLP methods and review clinical and research applications in the field of HF. We also propose several potential future directions of this emerging and rapidly evolving technological breakthrough.
自然语言处理（NLP）是机器学习/人工智能中一个蓬勃发展的领域，专注于人类语言的计算处理。研究人员和临床医生正在使用NLP方法，通过处理电子健康记录中大量以前未被利用的半结构化和非结构化文本数据，推动整个医学领域，特别是心力衰竭（HF）领域的发展。NLP在临床研究中有多种应用，包括显著改善队列组建、疾病表型分析和结局确定等流程。NLP还有潜力通过对HF患者的早期检测、准确诊断和循证管理来改善直接临床护理。在这篇前沿综述中，我们概述了NLP方法，并回顾了HF领域的临床和研究应用。我们还提出了这一新兴且快速发展的技术突破的几个潜在未来方向。
