This paper is in the following e-collection/theme issue:

Ontologies, Classifications, and Coding (164) Artificial Intelligence (665) Machine Learning (1004) Quality Improvement (159) Artificial Intelligence in Diabetes Care and Prevention (11)

Published on in Vol 8 , No 12 (2020) :December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/22649, first published .
Detecting Miscoded Diabetes Diagnosis Codes in Electronic Health Records for Quality Improvement: Temporal Deep Learning Approach

Detecting Miscoded Diabetes Diagnosis Codes in Electronic Health Records for Quality Improvement: Temporal Deep Learning Approach

Detecting Miscoded Diabetes Diagnosis Codes in Electronic Health Records for Quality Improvement: Temporal Deep Learning Approach

Authors of this article:

Sina Rashidian 1 Author Orcid Image ;   Kayley Abell-Hart 2 Author Orcid Image ;   Janos Hajagos 2 Author Orcid Image ;   Richard Moffitt 2 Author Orcid Image ;   Veena Lingam 2 Author Orcid Image ;   Victor Garcia 2 Author Orcid Image ;   Chao-Wei Tsai 2 Author Orcid Image ;   Fusheng Wang 1, 2 Author Orcid Image ;   Xinyu Dong 1 Author Orcid Image ;   Siao Sun 3 Author Orcid Image ;   Jianyuan Deng 2 Author Orcid Image ;   Rajarsi Gupta 2 Author Orcid Image ;   Joshua Miller 4 Author Orcid Image ;   Joel Saltz 2 Author Orcid Image ;   Mary Saltz 2 Author Orcid Image
Article Authors Cited by (1) Tweetations (4) Metrics

Books/Policy Documents

  1. Sun S, Wang F, Rashidian S, Kurc T, Abell-Hart K, Hajagos J, Zhu W, Saltz M, Saltz J. Heterogeneous Data Management, Polystores, and Analytics for Healthcare. View