Development and validation of a machine learning scoring system based on multi-dimensional metabolic signatures for invasive examination triage in intestinal diseases.
- DOI
- 10.3389/fgene.2026.1905165
- Published
- 2026
- Container
- Frontiers in genetics
- Publisher
- Not recorded
- Open access
- yes
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limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.3389/fgene.2026.1905165,
title = {Development and validation of a machine learning scoring system based on multi-dimensional metabolic signatures for invasive examination triage in intestinal diseases.},
author = {He J and Chen J and Zhang Y and Rao Y and He M and Zhu M},
year = {2026},
journal = {Frontiers in genetics},
doi = {10.3389/fgene.2026.1905165},
url = {https://doi.org/10.3389/fgene.2026.1905165}
}RIS
TY - JOUR TI - Development and validation of a machine learning scoring system based on multi-dimensional metabolic signatures for invasive examination triage in intestinal diseases. AU - He J AU - Chen J AU - Zhang Y AU - Rao Y AU - He M AU - Zhu M PY - 2026 JO - Frontiers in genetics DO - 10.3389/fgene.2026.1905165 UR - https://doi.org/10.3389/fgene.2026.1905165 ER -
APA
J, H., J, C., Y, Z., Y, R., M, H., & M, Z. (2026). Development and validation of a machine learning scoring system based on multi-dimensional metabolic signatures for invasive examination triage in intestinal diseases.. Frontiers in genetics. https://doi.org/10.3389/fgene.2026.1905165
Source records
- pubmed · retrieved 2026-09-25T06:47:33.188Z