Deep Learning Bridges the Diagnostic Gap in Chronic Endometritis – Medicina MDPI
Medicina MDPI shared a post on LinkedIn about a paper by Kotaro Kitayama et al. published in Medicina:
“Check out this highly cited paper:
Bridging the Diagnostic Gap between Histopathologic and Hysteroscopic Chronic Endometritis with Deep Learning Models by Kotaro Kitayama, Tadahiro Yasuo and Takeshi Yamaguchi
Read more.
11 Citation
Chronic endometritis (CE) is an inflammatory pathologic condition of the uterine mucosa characterized by unusual infiltration of CD138(+) endometrial stromal plasmacytes (ESPCs).
CE is often identified in infertile women with unexplained etiology, tubal factors, endometriosis, repeated implantation failure, and recurrent pregnancy loss.”
Title: Bridging the Diagnostic Gap between Histopathologic and Hysteroscopic Chronic Endometritis with Deep Learning Models
Authors: Kotaro Kitayama, Tadahiro Yasuo and Takeshi Yamaguchi
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