Oral manifestations in patients with coronavirus disease 2019 (COVID-19) identified using text mining: an observational study.

ABSTRACT: Text mining enables search, extraction, categorisation and information visualisation. This study aimed to identify oral manifestations in patients with COVID-19 using text mining to facilitate extracting relevant clinical information from a large set of publications. A list of publications from the open-access COVID-19 Open Research Dataset was downloaded using keywords related to oral health and dentistry. A total of 694,366 documents were retrieved. Filtering the articles using text mining yielded 1,554 oral health/dentistry papers. The list of articles was classified into five topics after applying a Latent Dirichlet Allocation (LDA) model. This classification was compared to the author's classification which yielded 17 categories. After a full-text review of articles in the category "O

SUBMITTER: Guauque-Olarte S 

PROVIDER: S-EPMC10584950 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature