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Prediction of preterm and low birth weight risk using a physiology based artificial neural network integrating hematological, dental, and periodontal index markers: a cross sectional study based on machine learning

Crossref DOI link: https://doi.org/10.1186/s12884-026-08955-z

Published Online: 2026-03-19

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

Authors

Temur, İsa

Özsan, Mehmet

Temur, Katibe Tuğçe

Çolak, Andaç Batur
License Information

Text and Data Mining valid from 2026-03-19

Version of Record valid from 2026-04-28
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Article History

Received: 22 July 2025

Accepted: 13 March 2026

First Online: 19 March 2026

Declarations

:

: This study was approved by the Non-Interventional Clinical Research Ethics Committee of Niğde Ömer Halisdemir University Faculty of Medicine (Decision No: 2022/17). Written informed consent was obtained from all participants prior to their inclusion in the study. All procedures performed involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

: Written informed consent was obtained from all participants for the publication of anonymized clinical and personal data. Documentation of the consent is available upon reasonable request.

: The authors declare no competing interests.

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