Interpretable machine learning methods based on oscillometry and electric modeling for the diagnostic of respiratory dysfunction in silicosis
- DOI
- 10.1186/s12911-026-03568-0
- Published
- 2026-05-16
- Container
- BMC Medical Informatics and Decision Making
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1186/s12911-026-03568-0,
title = {Interpretable machine learning methods based on oscillometry and electric modeling for the diagnostic of respiratory dysfunction in silicosis},
author = {Jorge Luís Machado do Amaral and Cíntia Moraes de Sá Sousa and Caroline de Oliveira Ribeiro and Paula Morisco de Sá and Agnaldo José Lopes and Pedro Lopes de Melo},
year = {2026},
journal = {BMC Medical Informatics and Decision Making},
doi = {10.1186/s12911-026-03568-0},
url = {https://doi.org/10.1186/s12911-026-03568-0}
}RIS
TY - JOUR TI - Interpretable machine learning methods based on oscillometry and electric modeling for the diagnostic of respiratory dysfunction in silicosis AU - Jorge Luís Machado do Amaral AU - Cíntia Moraes de Sá Sousa AU - Caroline de Oliveira Ribeiro AU - Paula Morisco de Sá AU - Agnaldo José Lopes AU - Pedro Lopes de Melo PY - 2026 JO - BMC Medical Informatics and Decision Making DO - 10.1186/s12911-026-03568-0 UR - https://doi.org/10.1186/s12911-026-03568-0 ER -
APA
Amaral, J. L. M. D., Sousa, C. M. D. S., Ribeiro, C. D. O., Sá, P. M. D., Lopes, A. J., & Melo, P. L. D. (2026). Interpretable machine learning methods based on oscillometry and electric modeling for the diagnostic of respiratory dysfunction in silicosis. BMC Medical Informatics and Decision Making. https://doi.org/10.1186/s12911-026-03568-0
Source records
- crossref · retrieved 2026-09-25T12:53:11.474Z