Random forest versus logistic regression: a large-scale benchmark experiment. - Raphaël Couronné; Philipp Probst; Anne-Laure Boulesteix (BMC Bioinform., 2018)

Riemannian Geometry Learning for Disease Progression Modelling. - Maxime Louis; Raphaël Couronné; Igor Koval; Benjamin Charlier; Stanley Durrleman (IPMI, 2019)

Learning Disease Progression Models With Longitudinal Data and Missing Values. - Raphaël Couronné; Marie Vidailhet; Jean-Christophe Corvol; Stéphane Lehéricy; Stanley Durrleman (ISBI, 2019)

Longitudinal Self-supervision to Disentangle Inter-patient Variability from Disease Progression. - Raphaël Couronné; Paul Vernhet; Stanley Durrleman (MICCAI (2), 2021)

Predicting the progression of mild cognitive impairment using machine learning: A systematic, quantitative and critical review. - Manon Ansart; Stéphane Epelbaum; Giulia Bassignana; Alexandre Bône; Simona Bottani; Tiziana Cattai; Raphaël Couronné; Johann Faouzi; Igor Koval; Maxime Louis; Elina Thibeau-Sutre; Junhao Wen 002; et al. (Medical Image Anal., 2021)

Progression models for Parkinson's Disease. (Modélisation de la progression de la maladie de Parkinson). - Raphaël Couronné (2021)