Classifying Pseudogout using Machine Learning Approaches with Electronic Health Record Data

OBJECTIVE: Identifying pseudogout in large datasets is difficult due to its episodic nature and lack of billing codes specific to this acute subtype of calcium pyrophosphate (CPP) deposition disease. We evaluated a novel machine learning approach for classifying pseudogout using electronic health re...

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Publié dans:Arthritis Care Res (Hoboken)
Auteurs principaux: Tedeschi, Sara K., Cai, Tianrun, He, Zeling, Ahuja, Yuri, Hong, Chuan, Yates, Katherine A., Dahal, Kumar, Xu, Chang, Lyu, Houchen, Yoshida, Kazuki, Solomon, Daniel H., Cai, Tianxi, Liao, Katherine P.
Format: Artigo
Langue:Inglês
Publié: 2021
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Article
Accès en ligne:https://ncbi.nlm.nih.gov/pmc/articles/PMC7338229/
https://ncbi.nlm.nih.gov/pubmed/31910317
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/acr.24132
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