Natural language processing: using artificial intelligence to understand human language in orthopedics

被引:19
作者
Pruneski, James A. [1 ]
Pareek, Ayoosh [2 ,4 ]
Nwachukwu, Benedict U. [2 ]
Martin, R. Kyle [3 ]
Kelly, Bryan T. [2 ]
Karlsson, Jon [4 ]
Pearle, Andrew D. [2 ]
Kiapour, Ata M. [1 ]
Williams, Riley J. [2 ]
机构
[1] Boston Childrens Hosp, Dept Orthoped Surg, Boston, MA USA
[2] Hosp Special Surg, Sports Med & Shoulder Serv, 535 East 70th St, New York, NY 10021 USA
[3] Univ Minnesota, Dept Orthoped Surg, Minneapolis, MN USA
[4] Gothenburg Univ, Sahlgrenska Univ Hosp, Sahlgrenska Acad, Dept Orthopaed, Gothenburg, 41124, Sweden
关键词
Artificial intelligence; Deep learning; Machine learning; Natural language processing; Predictive analytics; ARTHROPLASTY;
D O I
10.1007/s00167-022-07272-0
中图分类号
R826.8 [整形外科学]; R782.2 [口腔颌面部整形外科学]; R726.2 [小儿整形外科学]; R62 [整形外科学(修复外科学)];
学科分类号
摘要
Natural language processing (NLP) describes the broad field of artificial intelligence by which computers are trained to understand and generate human language. Within healthcare research, NLP is commonly used for variable extraction and classification/cohort identification tasks. While these tools are becoming increasingly popular and available as both open-source and commercial products, there is a paucity of the literature within the orthopedic space describing the key tasks within these powerful pipelines. Curation and navigation of the electronic medical record are becoming increasingly onerous, and it is important for physicians and other healthcare professionals to understand potential methods of harnessing this large data resource. The purpose of this study is to provide an overview of the tasks required to develop an NLP pipeline for orthopedic research and present recent examples of successful implementations.
引用
收藏
页码:1203 / 1211
页数:9
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