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Stéphane Epelbaum
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2020 – today
- 2021
- [j3]Clément Mantoux
, Baptiste Couvy-Duchesne
Understanding the Variability in Graph Data Sets through Statistical Modeling on the Stiefel Manifold. Entropy 23(4): 490 (2021) - [j2]Manon Ansart, Stéphane Epelbaum
Predicting the progression of mild cognitive impairment using machine learning: A systematic, quantitative and critical review. Medical Image Anal. 67: 101848 (2021) - [j1]Junhao Wen
Reproducible Evaluation of Diffusion MRI Features for Automatic Classification of Patients with Alzheimer's Disease. Neuroinformatics 19(1): 57-78 (2021) - 2020
- [i3]Alexandre Morin, Jorge Samper-González, Anne Bertrand, Sebastian Ströer, Didier Dormont, Aline Mendes, Pierrick Coupé
Accuracy of MRI Classification Algorithms in a Tertiary Memory Center Clinical Routine Cohort. CoRR abs/2003.09260 (2020)
2010 – 2019
- 2019
- [c2]Jorge Samper-González, Ninon Burgos
Reproducible evaluation of methods for predicting progression to Alzheimer's disease from clinical and neuroimaging data. Image Processing 2019: 109490V - 2018
- [i2]Claire Meyniel, Dalila Samri, Farah Stefano, Joel Crevoisier, Florence Bonté, Raffaella Migliaccio, Laure Delaby, Anne Bertrand, Marie Odile Habert, Bruno Dubois, Bahram Bodaghi, Stéphane Epelbaum:
COGEVIS: A New Scale to Evaluate Cognition in Patients with Visual Deficiency. CoRR abs/1812.07328 (2018) - [i1]Junhao Wen, Jorge Samper-González, Simona Bottani, Alexandre Routier, Ninon Burgos
Reproducible evaluation of diffusion MRI features for automatic classification of patients with Alzheimers disease. CoRR abs/1812.11183 (2018) - 2017
- [c1]Manon Ansart, Stéphane Epelbaum, Geoffroy Gagliardi
Prediction of Amyloidosis from Neuropsychological and MRI Data for Cost Effective Inclusion of Pre-symptomatic Subjects in Clinical Trials. DLMIA/ML-CDS@MICCAI 2017: 357-364
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