Impact of dataset partitioning on the reliability of SERS–machine learning models for antimicrobial resistance classification
- DOI
- 10.1016/j.aca.2026.346185
- Published
- 2026-11
- Container
- Analytica Chimica Acta
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.aca.2026.346185,
title = {Impact of dataset partitioning on the reliability of SERS–machine learning models for antimicrobial resistance classification},
author = {Zakarya Al-Shaebi and Munevver Akdeniz and Serra Ilayda Yerlitas Tastan and Pınar Sagiroğlu and Mustafa Altay Atalay and Gözde Erturk Zararsiz and Gökmen Zararsiz and Omer Aydin},
year = {2026},
journal = {Analytica Chimica Acta},
doi = {10.1016/j.aca.2026.346185},
url = {https://doi.org/10.1016/j.aca.2026.346185}
}RIS
TY - JOUR TI - Impact of dataset partitioning on the reliability of SERS–machine learning models for antimicrobial resistance classification AU - Zakarya Al-Shaebi AU - Munevver Akdeniz AU - Serra Ilayda Yerlitas Tastan AU - Pınar Sagiroğlu AU - Mustafa Altay Atalay AU - Gözde Erturk Zararsiz AU - Gökmen Zararsiz AU - Omer Aydin PY - 2026 JO - Analytica Chimica Acta DO - 10.1016/j.aca.2026.346185 UR - https://doi.org/10.1016/j.aca.2026.346185 ER -
APA
Al-Shaebi, Z., Akdeniz, M., Tastan, S. I. Y., Sagiroğlu, P., Atalay, M. A., Zararsiz, G. E., Zararsiz, G., & Aydin, O. (2026). Impact of dataset partitioning on the reliability of SERS–machine learning models for antimicrobial resistance classification. Analytica Chimica Acta. https://doi.org/10.1016/j.aca.2026.346185
Source records
- crossref · retrieved 2026-11-10T21:07:46.107Z