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

Ontologies, Classifications, and Coding (239) Artificial Intelligence (1371) Machine Learning (1465) Quality Improvement (253) Artificial Intelligence in Diabetes Care and Prevention (29)

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 Rashidian1 Author Orcid Image ;   Kayley Abell-Hart2 Author Orcid Image ;   Janos Hajagos2 Author Orcid Image ;   Richard Moffitt2 Author Orcid Image ;   Veena Lingam2 Author Orcid Image ;   Victor Garcia2 Author Orcid Image ;   Chao-Wei Tsai2 Author Orcid Image ;   Fusheng Wang1, 2 Author Orcid Image ;   Xinyu Dong1 Author Orcid Image ;   Siao Sun3 Author Orcid Image ;   Jianyuan Deng2 Author Orcid Image ;   Rajarsi Gupta2 Author Orcid Image ;   Joshua Miller4 Author Orcid Image ;   Joel Saltz2 Author Orcid Image ;   Mary Saltz2 Author Orcid Image
Article Authors Cited by (3) Tweetations (3) Metrics

Journals

  1. Saban M, Lutski M, Zucker I, Uziel M, Ben-Moshe D, Israel A, Vinker S, Golan-Cohen A, Laufer I, Green I, Eldor R, Merzon E. Identifying Diabetes Related-Complications in a Real-World Free-Text Electronic Medical Records in Hebrew Using Natural Language Processing Techniques. Journal of Diabetes Science and Technology 2024 View
  2. Tilhou A, Dague L, Chachlani P, Burns M, Ray M. Can telehealth expansion boost health care utilization specifically for patients with substance use disorders relative to patients with other types of chronic disease?. PLOS ONE 2024;19(4):e0299397 View

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