Artificial intelligence-augmented lesion recognition of peritoneal endometriosis: a novel technique.

Seckin TK, Kula H, Seckin TA

DOI: 10.1016/j.xfre.2026.04.012
Published: 2026 Aug
Container: F&S reports
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1016/j.xfre.2026.04.012,
  title = {Artificial intelligence-augmented lesion recognition of peritoneal endometriosis: a novel technique.},
  author = {Seckin TK and Kula H and Seckin TA},
  year = {2026},
  journal = {F\&S reports},
  doi = {10.1016/j.xfre.2026.04.012},
  url = {https://doi.org/10.1016/j.xfre.2026.04.012}
}

RIS

TY  - JOUR
TI  - Artificial intelligence-augmented lesion recognition of peritoneal endometriosis: a novel technique.
AU  - Seckin TK
AU  - Kula H
AU  - Seckin TA
PY  - 2026
JO  - F&S reports
DO  - 10.1016/j.xfre.2026.04.012
UR  - https://doi.org/10.1016/j.xfre.2026.04.012
ER  -

APA

TK, S., H, K., & TA, S. (2026). Artificial intelligence-augmented lesion recognition of peritoneal endometriosis: a novel technique.. F&S reports. https://doi.org/10.1016/j.xfre.2026.04.012

Source records

pubmed · retrieved 2026-09-26T13:11:29.333Z