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Deep Learning-Based Prediction of HRD From Histopathological Whole-Slide Images in Ovarian Cancer – IJGC
IJGC/LinkedIn
Jul 25, 2026, 10:23

Deep Learning-Based Prediction of HRD From Histopathological Whole-Slide Images in Ovarian Cancer – IJGC

International Journal of Gynecological Cancer (IJGC) shared a post on LinkedIn:

“New research introduces a deeplearning model designed to detect HRD in ovariancancer using standard H and E slides.”

Title: Deep learning-based prediction of homologous recombination deficiency from histopathological whole-slide images in ovarian cancer

Authors: Jean-Sébastien Frenel, Pierre-Etienne Heudel, Emmanuelle Guinaudeau, Céline Bossard, Gabriel Lindahl, Joseph Rynkiewicz, Sanae Salhi, Yahia Salhi, Jérôme Chetrit, Eric Pujade-Lauraine, Isabelle Ray-Coquard

Read the full article.

Deep Learning-Based Prediction of HRD From Histopathological Whole-Slide Images in Ovarian Cancer – IJGC

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Céline Bossard deeplearning model Emmanuelle Guinaudeau Eric Pujade-Lauraine Fertility Fertility News Gabriel Lindahl H and E slide HRD International Journal of Gynecological Cancer (IJGC) Isabelle Ray-Coquard Jean-Sébastien Frenel Jérôme Chetrit Joseph Rynkiewicz ovariancancer Pierre-Etienne Heudel reproductive health Reproductive Medicine Sanae Salhi Yahia Salhi
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