Deep Learning Models to Study the Early Stages of Parkinson's Disease. - Verónica Muñoz Ramírez; Virgilio Kmetzsch; Florence Forbes; Michel Dojat (ISBI, 2020)

A multimodal variational autoencoder for estimating progression scores from imaging and microRNA data in rare neurodegenerative diseases. - Virgilio Kmetzsch; Emmanuelle Becker; Dario Saracino; Vincent Anquetil; Daisy Rinaldi; Agnès Camuzat; Thomas Gareau; Isabelle Le Ber; Olivier Colliot (Image Processing, 2022)

Subtle anomaly detection: Application to brain MRI analysis of de novo Parkinsonian patients. - Verónica Muñoz Ramírez; Virgilio Kmetzsch; Florence Forbes; Sara Meoni; Elena Moro; Michel Dojat (Artif. Intell. Medicine, 2022)

Disease Progression Score Estimation From Multimodal Imaging and MicroRNA Data Using Supervised Variational Autoencoders. - Virgilio Kmetzsch; Emmanuelle Becker; Dario Saracino; Daisy Rinaldi; Agnès Camuzat; Isabelle Le Ber; Olivier Colliot (IEEE J. Biomed. Health Informatics, 2022)

Multimodal analysis of neuroimaging and transcriptomic data in genetic frontotemporal dementia. (Analyse multimodale des données de neuroimagerie et transcriptomiques dans la démence frontotemporale génétique). - Virgilio Kmetzsch (2022)