Research trends and evidence landscape of metabolomics and machine learning in the diagnosis of subclinical ketosis in dairy cows: a systematic review and bibliometric analysis
- DOI
- 10.1016/j.rvsc.2026.106368
- Published
- 2026-11
- Container
- Research in Veterinary Science
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.rvsc.2026.106368,
title = {Research trends and evidence landscape of metabolomics and machine learning in the diagnosis of subclinical ketosis in dairy cows: a systematic review and bibliometric analysis},
author = {Hoang Dao Dang and Jutarop Phetcharaburanin and Peerapol Sukon and Chaiyapas Thamrongyoswittayakul},
year = {2026},
journal = {Research in Veterinary Science},
doi = {10.1016/j.rvsc.2026.106368},
url = {https://doi.org/10.1016/j.rvsc.2026.106368}
}RIS
TY - JOUR TI - Research trends and evidence landscape of metabolomics and machine learning in the diagnosis of subclinical ketosis in dairy cows: a systematic review and bibliometric analysis AU - Hoang Dao Dang AU - Jutarop Phetcharaburanin AU - Peerapol Sukon AU - Chaiyapas Thamrongyoswittayakul PY - 2026 JO - Research in Veterinary Science DO - 10.1016/j.rvsc.2026.106368 UR - https://doi.org/10.1016/j.rvsc.2026.106368 ER -
APA
Dang, H. D., Phetcharaburanin, J., Sukon, P., & Thamrongyoswittayakul, C. (2026). Research trends and evidence landscape of metabolomics and machine learning in the diagnosis of subclinical ketosis in dairy cows: a systematic review and bibliometric analysis. Research in Veterinary Science. https://doi.org/10.1016/j.rvsc.2026.106368
Source records
- crossref · retrieved 2026-09-26T23:36:30.578Z