AI-DMRS: Prediction of Preclinical Multimorbidity Risk Through the Integration of Copper–Zinc Homeostasis, Inflammation, and Homocysteine Metabolism Using Explainable Artificial Intelligence

DOĞAN, T.AYDIN

Open source

DOI
10.5281/zenodo.23472487
Published
2026
Container
Not recorded
Publisher
Zenodo
Open access
yes

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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

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