| Statistical learning of spatiotemporal patterns from longitudinal manifold-valued networks I Koval, JB Schiratti, A Routier, M Bacci, O Colliot, S Allassonnière, ... International Conference on Medical Image Computing and Computer-Assisted …, 2017 | 21 | 2017 |
| Spatiotemporal propagation of the cortical atrophy: Population and individual patterns I Koval, JB Schiratti, A Routier, M Bacci, O Colliot, S Allassonnière, ... Frontiers in Neurology 9, 235, 2018 | 12 | 2018 |
| The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up RV Marinescu, NP Oxtoby, AL Young, EE Bron, AW Toga, MW Weiner, ... arXiv preprint arXiv:2002.03419, 2020 | 5 | 2020 |
| Riemannian geometry learning for disease progression modelling M Louis, R Couronne, I Koval, B Charlier, S Durrleman International Conference on Information Processing in Medical Imaging, 542-553, 2019 | 5 | 2019 |
| Simulating Alzheimer's disease progression with personalised digital brain models I Koval, A Bône, M Louis, S Bottani, A Marcoux, J Samper-Gonzalez, ... URL: https://hal. inria. fr/hal-01964821. preprint 580, 2018 | 3 | 2018 |
| Predicting the Progression of Mild Cognitive Impairment Using Machine Learning: A Systematic and Quantitative Review M Ansart, S Epelbaum, G Bassignana, A Bône, S Bottani, T Cattai, ... | 1 | 2019 |
| Awareness of cognitive decline through the continuum of Alzheimer’s disease and its association to APOE-ε4 and amyloid load F Cacciamani, A Valladier, E Maheux, I Koval, S Durrleman 2020 Alzheimer's Association International Conference, 2020 | | 2020 |
| Prediction of the MMSE up to 6 years ahead with cross-cohort replications E Maheux, I Koval, D Archetti, A Redolfi, S Durrleman 2020 Alzheimer's Association International Conference, 2020 | | 2020 |
| Towards cross-cohort estimation of cognitive decline in neurodegenerative diseases E Maheux, I Koval, D Archetti, A Redolfi, S Durrleman 2020 Alzheimer's Association International Conference, 2020 | | 2020 |
| Learning Multimodal Digital Models of Disease Progression from Longitudinal Data: Methods & Algorithms for the Description, Prediction and Simulation of Alzheimer’s Disease … I Koval Institut polytechnique de Paris, 2020 | | 2020 |
| Deciphering the progression of PET alterations using surface-based spatiotemporal modeling I Koval, A Marcoux, N Burgos, S Allassonnière, O Colliot, S Durrleman | | 2019 |
| Simulation of virtual cohorts increases predictive accuracy of cognitive decline in MCI subjects I Koval, S Allassonnière, S Durrleman arXiv preprint arXiv:1904.02921, 2019 | | 2019 |
| Design of a decision support system for predicting the progression of Alzheimer’s disease M Ansart, I Koval, A Bertrand, D Dormont, S Durrleman | | 2018 |
| Building disease progression models from longitudinal biomarkers C Fourrier, I Koval, S Bottani, O Colliot, S Durrleman 5th Annual Human Brain Project Summit, 2017 | | 2017 |
| Statistical Disease Progression Modeling in Alzheimer Disease NP Oxtoby, D Li, I Koval, LL Raket | | |
