A comprehensive maternal health risk prediction dataset from IoT-enabled medical cyber-physical systems in developing countries: supporting machine learning and deep learning applications for clinical decision support
- DOI
- 10.1186/s12911-026-03343-1
- Published
- 2026-02-12
- 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/s12911-026-03343-1,
title = {A comprehensive maternal health risk prediction dataset from IoT-enabled medical cyber-physical systems in developing countries: supporting machine learning and deep learning applications for clinical decision support},
author = {Mohammad Mobarak Hossain and Nasim Mahmud Nayan and Mohammod Abdul Kashem},
year = {2026},
journal = {BMC Medical Informatics and Decision Making},
doi = {10.1186/s12911-026-03343-1},
url = {https://doi.org/10.1186/s12911-026-03343-1}
}RIS
TY - JOUR TI - A comprehensive maternal health risk prediction dataset from IoT-enabled medical cyber-physical systems in developing countries: supporting machine learning and deep learning applications for clinical decision support AU - Mohammad Mobarak Hossain AU - Nasim Mahmud Nayan AU - Mohammod Abdul Kashem PY - 2026 JO - BMC Medical Informatics and Decision Making DO - 10.1186/s12911-026-03343-1 UR - https://doi.org/10.1186/s12911-026-03343-1 ER -
APA
Hossain, M. M., Nayan, N. M., & Kashem, M. A. (2026). A comprehensive maternal health risk prediction dataset from IoT-enabled medical cyber-physical systems in developing countries: supporting machine learning and deep learning applications for clinical decision support. BMC Medical Informatics and Decision Making. https://doi.org/10.1186/s12911-026-03343-1
Source records
- crossref · retrieved 2026-09-25T18:20:11.778Z