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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

Crossref DOI link: https://doi.org/10.1186/s12911-026-03343-1

Published Online: 2026-02-12

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Hossain, Mohammad Mobarak

Nayan, Nasim Mahmud

Kashem, Mohammod Abdul
License Information

Text and Data Mining valid from 2026-02-12

Version of Record valid from 2026-03-20
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Article History

Received: 19 August 2025

Accepted: 9 January 2026

First Online: 12 February 2026

Declarations

:

: This study received ethical approval from the Institutional Review Board of Dhaka University of Engineering & Technology, Gazipur (Approval No. [(DUET-IRB-2021-034], Date: [12122024]). All procedures conformed to the Declaration of Helsinki and local regulations. Written informed consent to participate was obtained from all participants prior to data collection.

: Written informed consent for publication of personal/clinical details and any potentially identifying images was obtained from all participants featured in figures (patient1.jpg, patient3.jpg, patient5.jpg). Where applicable, consent was obtained from a parent or legal guardian. Participants were informed of the implications of online publication.

: The authors declare no competing interests.

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