Comparison of Methods for Estimating Temporal Topic Models From Primary Care Clinical Text Data: Retrospective Closed Cohort Study

BackgroundHealth care organizations are collecting increasing volumes of clinical text data. Topic models are a class of unsupervised machine learning algorithms for discovering latent thematic patterns in these large unstructured document collections. ObjectiveWe...

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Autori principali:	Christopher Meaney, Michael Escobar, Therese A Stukel, Peter C Austin, Liisa Jaakkimainen
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	JMIR Publications 2022-12-01
Serie:	JMIR Medical Informatics
Accesso online:	https://medinform.jmir.org/2022/12/e40102
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