Open AccessForty-two Million Ways to Describe Pain: Topic Modeling of 200,000 PubMed Pain-Related Abstracts Using Natural Language Processing and Deep Learning–Based Text Generation
Author(s) -
Patrick J. Tighe,
Bharadwaj Sannapaneni,
Roger B. Fillingim,
Charles Doyle,
Michael Kent,
Ben Shickel,
Parisa Rashidi
Publication year - 2020
Publication title -
pain medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.893
H-Index - 97
eISSN - 1526-4637
pISSN - 1526-2375
DOI - 10.1093/pm/pnaa061
Subject(s) - word2vec , topic model , term (time) , natural language processing , artificial intelligence , outlier , computer science , deep learning , pain medicine , subject (documents) , latent dirichlet allocation , unified medical language system , medicine , information retrieval , psychiatry , world wide web , physics , embedding , quantum mechanics , anesthesiology
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