A scoping review of publicly available language tasks in clinical natural language processing
Published in Journal of the American Medical Informatics Association 29 (10), 1797-1806, 2022, 2022
Recommended citation: Yanjun Gao, Dmitriy Dligach, Leslie Christensen, Samuel Tesch, Ryan Laffin, Dongfang Xu, Timothy Miller, Ozlem Uzuner, Matthew M Churpek, and Majid Afshar. 2022. A scoping review of publicly available language tasks in clinical natural language processing. In Journal of the American Medical Informatics Association 29 (10), 1797-1806, 2022. https://pmc.ncbi.nlm.nih.gov/articles/PMC9471718/pdf/ocac127.pdf
Abstract:
Objective To provide a scoping review of papers on clinical natural language processing (NLP) shared tasks that use publicly available electronic health record data from a cohort of patients. Materials and Methods We searched 6 databases, including biomedical research and computer science literature databases. A round of title/abstract screening and full-text screening were conducted by 2 reviewers. Our method followed the PRISMA-ScR guidelines. Results A total of 35 papers with 48 clinical NLP tasks met inclusion criteria between 2007 and 2021. We categorized the tasks by the type of NLP problems, including named entity recognition, summarization, and other NLP tasks. Some tasks were introduced as potential clinical decision support applications, such as substance abuse detection, and phenotyping. We summarized the tasks by publication …