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Bienvenue sur la collection HAL du Bernoulli_Lab Bernoulli_Lab
Vous pouvez consulter et rechercher ici l'ensemble des publications des projets du laboratoire commun AP-HP - Inria Daniel Bernoulli.
Références
17
Derniers Dépôts
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Judith Abécassis, Théo Jolivet, Audrey Bergès, Elise Liu, Jean-Baptiste Julla, et al.. Operational challenges of building a million-patient cohort from EHRs: The COhort of DIabetic patients (CODIA) on the AP-HP EDS. journée de l'Atelier TIDS (Traitement Informatique des Données de Santé) du GdR MaDICS, Oct 2024, Paris (PariSanté Campus), France. ⟨hal-04817434⟩
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Jérôme Diaz, François Kimmig, Fabrice Vallée, Arthur Le Gall, Romain Kirszenblat, et al.. Modeling-based Radial Pressure Waveform Reconstruction Using Photoplethysmography Signals. CinC 2024 - 51st international Computing in Cardiology Conference, Sep 2024, Karlsruhe, Germany. ⟨10.22489/CinC.2024.332⟩. ⟨hal-04870802⟩
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Sophie Loizillon, Yannick Jacob, Aurelien Maire, Didier Dormont, Olivier Colliot, et al.. Detecting Brain Anomalies in Clinical Routine with the β-VAE: Feasibility Study on Age-Related White Matter Hyperintensities. Medical Imaging with Deep Learning - MIDL 2024, Jul 2024, Paris, France. ⟨hal-04674025⟩
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Sophie Loizillon, Simona Bottani, Stéphane Mabille, Yannick Jacob, Aurélien Maire, et al.. Automated MRI Quality Assessment of Brain T1-weighted MRI in Clinical Data Warehouses: A Transfer Learning Approach Relying on Artefact Simulation. Journal of Machine Learning for Biomedical Imaging, 2024, 2 (June 2024), pp.888-915. ⟨10.59275/j.melba.2024-7fgd⟩. ⟨hal-04623223⟩
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Sophie Loizillon, Simona Bottani, Aurélien Maire, Sebastian Ströer, Didier Dormont, et al.. Automatic motion artefact detection in brain T1-weighted magnetic resonance images from a clinical data warehouse using synthetic data. Medical Image Analysis, 2024, 93, pp.103073. ⟨10.1016/j.media.2023.103073⟩. ⟨hal-03910451v2⟩
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