Mapping toxicity pathways of per- and polyfluoroalkyl substances using interpretable classification-based machine learning models.
- DOI
- 10.1080/1062936x.2026.2693300
- Published
- 2026 Jun 29
- Container
- SAR and QSAR in environmental research
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1080/1062936x.2026.2693300,
title = {Mapping toxicity pathways of per- and polyfluoroalkyl substances using interpretable classification-based machine learning models.},
author = {Sarkar S and Pore S and Roy K},
year = {2026},
journal = {SAR and QSAR in environmental research},
doi = {10.1080/1062936x.2026.2693300},
url = {https://doi.org/10.1080/1062936x.2026.2693300}
}RIS
TY - JOUR TI - Mapping toxicity pathways of per- and polyfluoroalkyl substances using interpretable classification-based machine learning models. AU - Sarkar S AU - Pore S AU - Roy K PY - 2026 JO - SAR and QSAR in environmental research DO - 10.1080/1062936x.2026.2693300 UR - https://doi.org/10.1080/1062936x.2026.2693300 ER -
APA
S, S., S, P., & K, R. (2026). Mapping toxicity pathways of per- and polyfluoroalkyl substances using interpretable classification-based machine learning models.. SAR and QSAR in environmental research. https://doi.org/10.1080/1062936x.2026.2693300
Source records
- pubmed · retrieved 2026-09-26T14:18:25.530Z