Jean-Eudes Le Douget

Deep Learning on Histologic Slides Accurately Predicts Consensus Molecular Subtypes and Spatial Heterogeneity in Colon Cancer

Jean-Eudes Le Douget, Paul Mazhuvanchary Jacob, Côme Lepage, Claire Gallois et autres

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Deep learning uncovers histological patterns of YAP1/TEAD activity related to disease aggressiveness in cancer patients

Benoît Schmauch, Vincent Cabeli, Omar Darwiche Domingues, Jean-Eudes Le Douget et autres

-family genes. Recent works have highlighted the role of YAP1/TEAD activity in several cancers and its potential therapeutic implications. Therefore, identifying patients with a dysregulated Hippo pathway is key to enhancing treatment impact. Although recent studies have derived RNA-seq-based signatures, there remains …

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Deep learning uncovers histological patterns of YAP1/TEAD activity related to disease aggressiveness in cancer patients

Benoît Schmauch, Vincent Cabeli, Omar Darwiche Domingues, Jean-Eudes Le Douget et autres

Summary Over the last decade, Hippo signaling has emerged as a major tumor-suppressing pathway. Its dysregulation is associated with abnormal expression of YAP1 and TEAD -family genes. Recent works have highlighted the role of YAP1/TEAD activity in several cancers and its potential …

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Abstract 7377: Deep learning uncovers morphological patterns of YAP1/TEAD activity related to disease aggressiveness in cancer patients

Benoît Schmauch, Vincent Cabeli, Omar Darwiche-Domingues, Jean-Eudes Le Douget et autres

Abstract Hippo signaling emerged over the last decade as a major tumor-suppressing pathway. Its dysregulation is generally associated with abnormal expression levels of YAP1, WWTR1 (coding for the TAZ protein) and TEAD genes among others. This pathway has been shown to have …

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Abstract 5430: Improved colorectal cancer survival prediction with deep learning-based WSI analysis on PETACC8 and PRODIGE13 cohorts

Jean-Eudes Le Douget, Julien Taı̈eb, Paul Mazhuvanchary Jacob, Frédéric Bibeau et autres

Abstract Colorectal cancer (CRC) is the third most common cancer worldwide and represents the third leading cause of cancer deaths. Robust postoperative prediction of CRC patient prognosis may prove useful to better stratify patients, guide therapeutic choices and improve clinical trial designs. …

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Application of deep learning models on whole slide images uncover new histological markers related to high-risk malignant pleural mesothelioma.

Douglas J. Hartman, Jean-Eudes Le Douget, Ye Ye, Yaming Li et autres

e13580 Background: Malignant Pleural mesothelioma (MPM) is a highly aggressive cancer of the pleural surface and represents 80-90% of mesothelioma diagnosis. MPM is broadly subclassified into three histological subgroups (epithelioid, sarcomatoid, biphasic), however tissue heterogeneity has resulted in diagnostic challenges and suboptimal …

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An ensemble learning approach to detect epileptic seizures from long intracranial EEG recordings

Jean-Baptiste Schiratti, Jean-Eudes Le Douget, Michel Le Van Quyen, Slim Essid et autres

International audience

An Ensemble Learning Approach to Detect Epileptic Seizures from Long Intracranial EEG Recordings

Jean-Baptiste Schiratti, Jean-Eudes Le Douget, Michel Le Van Quyen, Slim Essid et autres

This paper proposes a patient-specific supervised classification algorithm to detect seizures in long offline intracranial electroencephalographic (iEEG) recordings. The main idea of the proposed algorithm is to combine a set of probabilistic classifiers, trained on a dataset of 1 s epochs, into …

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