Estimating weaning duration from incremental dentine δ15N and δ13C using a sequence-based LSTM neural network: A deep learning framework for bioarchaeological applications.

Ganiatsou E, Souleles A, Papageorgopoulou C

DOI: 10.1371/journal.pone.0337619
Published: 2025
Container: PloS one
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1371/journal.pone.0337619,
  title = {Estimating weaning duration from incremental dentine δ15N and δ13C using a sequence-based LSTM neural network: A deep learning framework for bioarchaeological applications.},
  author = {Ganiatsou E and Souleles A and Papageorgopoulou C},
  year = {2025},
  journal = {PloS one},
  doi = {10.1371/journal.pone.0337619},
  url = {https://doi.org/10.1371/journal.pone.0337619}
}

RIS

TY  - JOUR
TI  - Estimating weaning duration from incremental dentine δ15N and δ13C using a sequence-based LSTM neural network: A deep learning framework for bioarchaeological applications.
AU  - Ganiatsou E
AU  - Souleles A
AU  - Papageorgopoulou C
PY  - 2025
JO  - PloS one
DO  - 10.1371/journal.pone.0337619
UR  - https://doi.org/10.1371/journal.pone.0337619
ER  -

APA

E, G., A, S., & C, P. (2025). Estimating weaning duration from incremental dentine δ15N and δ13C using a sequence-based LSTM neural network: A deep learning framework for bioarchaeological applications.. PloS one. https://doi.org/10.1371/journal.pone.0337619

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pubmed · retrieved 2026-09-26T04:39:27.684Z