Deep learning-based automated classification of endometrial lesions in IVF patients using hysteroscopic images.

Barakat M, Massoud R, Alhalabi M

DOI: 10.1038/s41598-026-57032-0
Published: 2026 Jun 6
Container: Scientific reports
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1038/s41598-026-57032-0,
  title = {Deep learning-based automated classification of endometrial lesions in IVF patients using hysteroscopic images.},
  author = {Barakat M and Massoud R and Alhalabi M},
  year = {2026},
  journal = {Scientific reports},
  doi = {10.1038/s41598-026-57032-0},
  url = {https://doi.org/10.1038/s41598-026-57032-0}
}

RIS

TY  - JOUR
TI  - Deep learning-based automated classification of endometrial lesions in IVF patients using hysteroscopic images.
AU  - Barakat M
AU  - Massoud R
AU  - Alhalabi M
PY  - 2026
JO  - Scientific reports
DO  - 10.1038/s41598-026-57032-0
UR  - https://doi.org/10.1038/s41598-026-57032-0
ER  -

APA

M, B., R, M., & M, A. (2026). Deep learning-based automated classification of endometrial lesions in IVF patients using hysteroscopic images.. Scientific reports. https://doi.org/10.1038/s41598-026-57032-0

Source records

pubmed · retrieved 2026-09-26T21:49:50.246Z