A Hybrid and Comparative Machine Learning Framework for Predicting Gestational Diabetes Mellitus via a Prospective Case-Control Design: A Pilot Study Integrating Periodontal Health and Hematological Inflammatory Markers
- DOI
- 10.3390/metabo16090617
- Published
- 2026-08-27
- Container
- Metabolites
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/metabo16090617,
title = {A Hybrid and Comparative Machine Learning Framework for Predicting Gestational Diabetes Mellitus via a Prospective Case-Control Design: A Pilot Study Integrating Periodontal Health and Hematological Inflammatory Markers},
author = {İsa Temur and Mehmet Özsan and Katibe Tuğçe Temur and Andaç Batur Çolak},
year = {2026},
journal = {Metabolites},
doi = {10.3390/metabo16090617},
url = {https://doi.org/10.3390/metabo16090617}
}RIS
TY - JOUR TI - A Hybrid and Comparative Machine Learning Framework for Predicting Gestational Diabetes Mellitus via a Prospective Case-Control Design: A Pilot Study Integrating Periodontal Health and Hematological Inflammatory Markers AU - İsa Temur AU - Mehmet Özsan AU - Katibe Tuğçe Temur AU - Andaç Batur Çolak PY - 2026 JO - Metabolites DO - 10.3390/metabo16090617 UR - https://doi.org/10.3390/metabo16090617 ER -
APA
Temur, İ., Özsan, M., Temur, K. T., & Çolak, A. B. (2026). A Hybrid and Comparative Machine Learning Framework for Predicting Gestational Diabetes Mellitus via a Prospective Case-Control Design: A Pilot Study Integrating Periodontal Health and Hematological Inflammatory Markers. Metabolites. https://doi.org/10.3390/metabo16090617
Source records
- crossref · retrieved 2026-09-25T08:35:32.921Z