AI-DMRS: Prediction of Preclinical Multimorbidity Risk Through the Integration of Copper–Zinc Homeostasis, Inflammation, and Homocysteine Metabolism Using Explainable Artificial Intelligence
- DOI
- 10.5281/zenodo.23472487
- Published
- 2026
- Container
- Not recorded
- Publisher
- Zenodo
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.5281/zenodo.23472487,
title = {AI-DMRS: Prediction of Preclinical Multimorbidity Risk Through the Integration of Copper–Zinc Homeostasis, Inflammation, and Homocysteine Metabolism Using Explainable Artificial Intelligence},
author = {DOĞAN, T.AYDIN},
year = {2026},
doi = {10.5281/zenodo.23472487},
url = {https://doi.org/10.5281/zenodo.23472487}
}RIS
TY - JOUR TI - AI-DMRS: Prediction of Preclinical Multimorbidity Risk Through the Integration of Copper–Zinc Homeostasis, Inflammation, and Homocysteine Metabolism Using Explainable Artificial Intelligence AU - DOĞAN, T.AYDIN PY - 2026 DO - 10.5281/zenodo.23472487 UR - https://doi.org/10.5281/zenodo.23472487 ER -
APA
T.AYDIN, D. (2026). AI-DMRS: Prediction of Preclinical Multimorbidity Risk Through the Integration of Copper–Zinc Homeostasis, Inflammation, and Homocysteine Metabolism Using Explainable Artificial Intelligence. https://doi.org/10.5281/zenodo.23472487
Source records
- datacite · retrieved 2026-11-10T08:53:43.212Z