Search Results - "Schiratti, Jean Baptiste"

A deep learning method for predicting knee osteoarthritis radiographic progression from MRI by Schiratti, Jean-Baptiste, Dubois, Rémy, Herent, Paul, Cahané, David, Dachary, Jocelyn, Clozel, Thomas, Wainrib, Gilles, Keime-Guibert, Florence, Lalande, Agnes, Pueyo, Maria, Guillier, Romain, Gabarroca, Christine, Moingeon, Philippe

“…Background The identification of patients with knee osteoarthritis (OA) likely to progress rapidly in terms of structure is critical to facilitate the…”
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Spatiotemporal Propagation of the Cortical Atrophy: Population and Individual Patterns by Koval, Igor, Schiratti, Jean-Baptiste, Routier, Alexandre, Bacci, Michael, Colliot, Olivier, Allassonnière, Stéphanie, Durrleman, Stanley

“…Repeated failures in clinical trials for Alzheimer's disease (AD) have raised a strong interest for the prodromal phase of the disease. A better understanding…”
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Semiautomated segmentation of hepatocellular carcinoma tumors with MRI using convolutional neural networks by Said, Daniela, Carbonell, Guillermo, Stocker, Daniel, Hectors, Stefanie, Vietti-Violi, Naik, Bane, Octavia, Chin, Xing, Schwartz, Myron, Tabrizian, Parissa, Lewis, Sara, Greenspan, Hayit, Jégou, Simon, Schiratti, Jean-Baptiste, Jehanno, Paul, Taouli, Bachir

“…Objective To assess the performance of convolutional neural networks (CNNs) for semiautomated segmentation of hepatocellular carcinoma (HCC) tumors on MRI…”
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An artificial intelligence model predicts the survival of solid tumour patients from imaging and clinical data by Schutte, Kathryn, Brulport, Fabien, Harguem-Zayani, Sana, Schiratti, Jean-Baptiste, Ghermi, Ridouane, Jehanno, Paul, Jaeger, Alexandre, Alamri, Talal, Naccache, Raphaël, Haddag-Miliani, Leila, Orsi, Teresa, Lamarque, Jean-Philippe, Hoferer, Isaline, Lawrance, Littisha, Benatsou, Baya, Bousaid, Imad, Azoulay, Mikael, Verdon, Antoine, Bidault, François, Balleyguier, Corinne, Aubert, Victor, Bendjebbar, Etienne, Maussion, Charles, Loiseau, Nicolas, Schmauch, Benoît, Sefta, Meriem, Wainrib, Gilles, Clozel, Thomas, Ammari, Samy, Lassau, Nathalie

“…The need for developing new biomarkers is increasing with the emergence of many targeted therapies. Artificial Intelligence (AI) algorithms have shown great…”
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Integrating deep learning CT-scan model, biological and clinical variables to predict severity of COVID-19 patients by Lassau, Nathalie, Ammari, Samy, Chouzenoux, Emilie, Gortais, Hugo, Herent, Paul, Devilder, Matthieu, Soliman, Samer, Meyrignac, Olivier, Talabard, Marie-Pauline, Lamarque, Jean-Philippe, Dubois, Remy, Loiseau, Nicolas, Trichelair, Paul, Bendjebbar, Etienne, Garcia, Gabriel, Balleyguier, Corinne, Merad, Mansouria, Stoclin, Annabelle, Jegou, Simon, Griscelli, Franck, Tetelboum, Nicolas, Li, Yingping, Verma, Sagar, Terris, Matthieu, Dardouri, Tasnim, Gupta, Kavya, Neacsu, Ana, Chemouni, Frank, Sefta, Meriem, Jehanno, Paul, Bousaid, Imad, Boursin, Yannick, Planchet, Emmanuel, Azoulay, Mikael, Dachary, Jocelyn, Brulport, Fabien, Gonzalez, Adrian, Dehaene, Olivier, Schiratti, Jean-Baptiste, Schutte, Kathryn, Pesquet, Jean-Christophe, Talbot, Hugues, Pronier, Elodie, Wainrib, Gilles, Clozel, Thomas, Barlesi, Fabrice, Bellin, Marie-France, Blum, Michael G. B.

“…The SARS-COV-2 pandemic has put pressure on intensive care units, so that identifying predictors of disease severity is a priority. We collect 58 clinical and…”
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MYC Rearrangement Prediction From LYSA Whole Slide Images in Large B-Cell Lymphoma: A Multicentric Validation of Self-supervised Deep Learning Models by Syrykh, Charlotte, Di Proietto, Valentina, Brion, Eliott, Copie-Bergman, Christiane, Jardin, Fabrice, Dartigues, Peggy, Gaulard, Philippe, Molina, Thierry Jo, Briere, Josette, Oberic, Lucie, Haioun, Corine, Tilly, Hervé, Maussion, Charles, Morel, Mehdi, Schiratti, Jean-Baptiste, Laurent, Camille

“…Large B-cell lymphoma (LBCL) is a heterogeneous lymphoid malignancy in which MYC gene rearrangement (MYC-R) is associated with a poor prognosis, prompting the…”
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Statistical learning of spatiotemporal patterns from longitudinal manifold-valued networks by Koval, Igor, Schiratti, Jean-Baptiste, Routier, Alexandre, Bacci, Michael, Colliot, Olivier, Allassonnière, Stéphanie, Durrleman, Stanley

“…Proc. Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017, Lecture Notes in Computer Science, volume 10433, pp 451-459, Springer We…”
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MOSAIC: Multi-Omic Spatial Atlas in Cancer, effect on precision oncology by Lehar, Joseph, Madissoon, Elo, Chevallier, Jerome, Schiratti, Jean Baptiste, Kamburov, Atanas, Barnes, Rodrigo, Haignere, Carla, Joy, Anna, Dodacki, Agnès, Hoffmann, Caroline, Lopez Lastra, Silvia, Espin Perez, Almudena, Bayard, Quentin, von Loga, Katharina, Chaperon, Hubert, Vert, Jean-Philippe, Durand, Eric, Soumelis, Vassili, Wainrib, Gilles, Clozel, Thomas

“…e15076 Background: Precision oncology aims to first break diagnoses into biologically distinct subtypes, then pursue personalized therapies for each group of…”
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MYC Rearrangement Prediction from LYSA Whole Slide Images in Large B-cell Lymphoma: A Multi-centric Validation of Self-supervised Deep Learning Models by Syrykh, Charlotte, DI Proietto, Valentina, Brion, Eliott, Copie-Bergman, Christiane, Jardin, Fabrice, Dartigues, Peggy, Gaulard, Philippe, Jo Molina, Thierry, Briere, Josette, Oberic, Lucie, Haioun, Corine, Tilly, Hervé, Maussion, Charles, Morel, Mehdi, Schiratti, Jean-Baptiste, Laurent, Camille

“…Large B-cell lymphoma (LBCL) is a heterogeneous lymphoid malignancy in which MYC gene rearrangement (MYC-R) is associated with a poor prognosis, prompting the…”
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Abdominal musculature segmentation and surface prediction from CT using deep learning for sarcopenia assessment by Blanc-Durand, P., Schiratti, J.-B., Schutte, K., Jehanno, P., Herent, P., Pigneur, F., Lucidarme, O., Benaceur, Y., Sadate, A., Luciani, A., Ernst, O., Rouchaud, A., Creze, M., Dallongeville, A., Banaste, N., Cadi, M., Bousaid, I., Lassau, N., Jegou, S.

“…The purpose of this study was to build and train a deep convolutional neural networks (CNN) algorithm to segment muscular body mass (MBM) to predict muscular…”
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Abstract 1924: PULS-AI: A multimodal artificial intelligence model to predict survival of solid tumor patients treated with antiangiogenics by Schutte, Kathryn, Brulport, Fabien, Harguem-Zayani, Sana, Schiratti, Jean-Baptiste, Ghermi, Ridouane, Jehanno, Paul, Jaeger, Alexandre, Alamri, Talal, Naccache, Raphael, Haddag-Miliani, Leila, Orsi, Teresa, Lamarque, Jean-Philippe, Hoferer, Isaline, Lawrance, Littisha, Benatsou, Baya, Bousaid, Imad, Azoulay, Mickael, Verdon, Antoine, Bidault, François, Balleyguier, Corinne, Aubert, Victor, Bendjebbar, Etienne, Maussion, Charles, Loiseau, Nicolas, Schmauch, Benoit, Sefta, Meriem, Wainrib, Gilles, Clozel, Thomas, Ammari, Samy, Lassau, Nathalie

“…The need for developing new biomarkers is increasing with the emergence of many targeted therapies. In this study, we used artificial intelligence (AI) to…”
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A Mixed-Effects Model with Time Reparametrization for Longitudinal Univariate Manifold-Valued Data by Schiratti, J B, Allassonnière, S, Routier, A, Durrleman, S

“…Mixed-effects models provide a rich theoretical framework for the analysis of longitudinal data. However, when used to analyze or predict the progression of a…”
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Using StyleGAN for Visual Interpretability of Deep Learning Models on Medical Images by Schutte, Kathryn, Moindrot, Olivier, Hérent, Paul, Schiratti, Jean-Baptiste, Jégou, Simon

“…As AI-based medical devices are becoming more common in imaging fields like radiology and histology, interpretability of the underlying predictive models is…”
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