Bobba Pratheek S, Sailer Anne, Pruneski James A, Beck Spencer, Mozayan Ali, Mozayan Sara, Arango Jennifer, Cohan Arman, Chheang Sophie
Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States.
Harvard Medical School, Boston, MA, United States.
Clin Imaging. 2023 May;97:55-61. doi: 10.1016/j.clinimag.2023.02.014. Epub 2023 Mar 5.
Natural language processing (NLP) is a wide range of techniques that allows computers to interact with human text. Applications of NLP in everyday life include language translation aids, chat bots, and text prediction. It has been increasingly utilized in the medical field with increased reliance on electronic health records. As findings in radiology are primarily communicated via text, the field is particularly suited to benefit from NLP based applications. Furthermore, rapidly increasing imaging volume will continue to increase burden on clinicians, emphasizing the need for improvements in workflow. In this article, we highlight the numerous non-clinical, provider focused, and patient focused applications of NLP in radiology. We also comment on challenges associated with development and incorporation of NLP based applications in radiology as well as potential future directions.
自然语言处理(NLP)是一系列广泛的技术,它使计算机能够与人类文本进行交互。NLP在日常生活中的应用包括语言翻译辅助工具、聊天机器人和文本预测。随着对电子健康记录的依赖增加,它在医学领域的应用也越来越广泛。由于放射学中的发现主要通过文本进行交流,该领域特别适合受益于基于NLP的应用。此外,成像量的迅速增加将继续增加临床医生的负担,这突出了改进工作流程的必要性。在本文中,我们重点介绍了NLP在放射学中的众多非临床、以提供者为中心和以患者为中心的应用。我们还评论了与放射学中基于NLP的应用的开发和整合相关的挑战以及潜在的未来方向。