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Algorithmic identification of atypical diabetes in electronic health record (EHR) systems
- Sara J. Cromer ,
- Victoria Chen ,
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Christopher Han,
Roles Data curation
Affiliations Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, Massachusetts, United States of America, Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
⨯ - William Marshall,
- Shekina Emongo,
- Evelyn Greaux,
- Tim Majarian,
- Jose C. Florez,
- Josep Mercader,
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Miriam S. Udler
Contributed equally to this work with: Sara J. Cromer, Victoria Chen, Miriam S. Udler
Roles Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Visualization, Writing – original draft, Writing – review & editing
* E-mail: mudler@mgh.harvard.edu
Affiliations Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, Massachusetts, United States of America, Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America, Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America, Northeastern University, Boston, Massachusetts, United States of America, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America
⨯
https://orcid.org/0000-0002-1585-4370
Algorithmic identification of atypical diabetes in electronic health record (EHR) systems
- Sara J. Cromer,
- Victoria Chen,
- Christopher Han,
- William Marshall,
- Shekina Emongo,
- Evelyn Greaux,
- Tim Majarian,
- Jose C. Florez,
- Josep Mercader,
- Miriam S. Udler
- Published: December 12, 2022
- https://doi.org/10.1371/journal.pone.0278759