Estimating the Charlson Comorbidity Index From Privacy-Truncated Diagnosis Codes: Methodological Quantitative Study Evaluating Computational Strategies in 507,949 Inpatient Encounters (Preprint)
- DOI
- 10.2196/107041
- Published
- 2026-07-14
- Container
- JMIR Medical Informatics
- Publisher
- JMIR Publications Inc.
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.2196/107041,
title = {Estimating the Charlson Comorbidity Index From Privacy-Truncated Diagnosis Codes: Methodological Quantitative Study Evaluating Computational Strategies in 507,949 Inpatient Encounters (Preprint)},
author = {Gaetan Kamdje Wabo and Piotr Pawel Sokolowski and Mahboubeh Jannesari Ladani and Nandhini Santhanam and Michael Hagmann and Thomas Ganslandt and Fabian Siegel},
year = {2026},
journal = {JMIR Medical Informatics},
doi = {10.2196/107041},
url = {https://doi.org/10.2196/107041}
}RIS
TY - JOUR TI - Estimating the Charlson Comorbidity Index From Privacy-Truncated Diagnosis Codes: Methodological Quantitative Study Evaluating Computational Strategies in 507,949 Inpatient Encounters (Preprint) AU - Gaetan Kamdje Wabo AU - Piotr Pawel Sokolowski AU - Mahboubeh Jannesari Ladani AU - Nandhini Santhanam AU - Michael Hagmann AU - Thomas Ganslandt AU - Fabian Siegel PY - 2026 JO - JMIR Medical Informatics DO - 10.2196/107041 UR - https://doi.org/10.2196/107041 ER -
APA
Wabo, G. K., Sokolowski, P. P., Ladani, M. J., Santhanam, N., Hagmann, M., Ganslandt, T., & Siegel, F. (2026). Estimating the Charlson Comorbidity Index From Privacy-Truncated Diagnosis Codes: Methodological Quantitative Study Evaluating Computational Strategies in 507,949 Inpatient Encounters (Preprint). JMIR Medical Informatics. https://doi.org/10.2196/107041
Source records
- crossref · retrieved 2026-11-08T18:20:36.697Z