TY - CHAP M1 - Book, Section TI - Natural Language Processing and Artificial Intelligence for Clinical Documentation A1 - Ting, David Y. A2 - Hashimoto, MD, MS, Daniel A. A2 - Meireles, MD, Ozanan R. A2 - Rosman, PhD, Guy Y1 - 2021 N1 - T2 - Artificial Intelligence in Surgery: Understanding the Role of AI in Surgical Practice AB - HIGHLIGHTSCurrently, most of the data in electronic health records reside in free-text documentation—often unstructured—that is useless for artificial intelligence (AI) training without preprocessing.Natural language processing (NLP) plays the dual function in health care AI of unlocking meaning from free-text and other unstructured documentation while also advancing and improving the creation of clinical documentation in the first place.Regarding the capture of data, NLP-based applications (eg, computerized voice recognition, clinical documentation improvement, ambient voice assistants, and ambient virtual scribes) have proven their ability to decrease the burden of clinicians in producing clinical documentation.Regarding the curation of data on the back end, NLP provides the mechanism that transforms clinical data from an amorphous and unhelpful state to a form that makes deep insight and explainable AI possible. These NLP use cases include data mining research, computer-assisted coding, automated registry reporting, clinical trial matching, prior authorization, clinical decision support, risk adjustment and hierarchical condition category (HCC) coding, computational phenotyping and biomarker discovery, and population surveillance. SN - PB - McGraw-Hill Education CY - New York, NY Y2 - 2024/03/29 UR - accesssurgery.mhmedical.com/content.aspx?aid=1180350574 ER -