| Discrete changes in glucose metabolism define aging S Ravera, M Podestà, F Sabatini, M Dagnino, D Cilloni, S Fiorini, A Barla, ... Scientific reports 9 (1), 10347, 2019 | 81 | 2019 |
| The hidden information in patient-reported outcomes and clinician-assessed outcomes: multiple sclerosis as a proof of concept of a machine learning approach G Brichetto, M Monti Bragadin, S Fiorini, MA Battaglia, G Konrad, ... Neurological sciences 41 (2), 459-462, 2020 | 40 | 2020 |
| A machine learning pipeline for multiple sclerosis course detection from clinical scales and patient reported outcomes S Fiorini, A Verri, A Tacchino, M Ponzio, G Brichetto, A Barla 2015 37th Annual International Conference of the IEEE engineering in …, 2015 | 40 | 2015 |
| Automatic Generation of Synthetic Retinal Fundus Images. S Fiorini, L Ballerini, E Trucco, A Ruggeri MIUA, 7-12, 2014 | 39 | 2014 |
| Predicting diabetes second-line therapy initiation in the Australian population via timespan-guided neural attention network S Fiorini, F Hajati, A Barla, F Girosi BioRxiv, 529933, 2019 | 24 | 2019 |
| Data-driven strategies for robust forecast of continuous glucose monitoring time-series S Fiorini, C Martini, D Malpassi, R Cordera, D Maggi, A Verri, A Barla Engineering in Medicine and Biology Society (EMBC), 2017 39th Annual …, 2017 | 14 | 2017 |
| Temporal prediction of multiple sclerosis evolution from patient-centered outcomes S Fiorini, A Verri, A Barla, A Tacchino, G Brichetto Proceedings of the 2nd Machine Learning for Healthcare Conference 68, 112-125, 2017 | 9 | 2017 |
| PALLADIO: a parallel framework for robust variable selection in high-dimensional data M Barbieri, S Fiorini, F Tomasi, A Barla Python for High-Performance and Scientific Computing (PyHPC), Workshop on, 19-26, 2016 | 7 | 2016 |
| Where do we stand in regularization for life science studies? V Tozzo, C Azencott, S Fiorini, E Fava, A Trucco, A Barla Journal of Computational Biology 29 (3), 213-232, 2022 | 6 | 2022 |
| Multiple sclerosis disease course prediction: a machine learning model based on patient reported and clinician assessed outcomes A Tacchino, S Fiorini, M Ponzio, A Barla, A Verri, MA Battaglia, G Brichetto ECTRIMS 2017, Paris (FR), 2017 | 2 | 2017 |
| Adenine: A HPC-Oriented Tool for Biological Data Exploration S Fiorini, F Tomasi, M Squillario, A Barla International Meeting on Computational Intelligence Methods for …, 2017 | 1 | 2017 |
| A temporal model for multiple sclerosis course evolution S Fiorini, A Tacchino, G Brichetto, A Verri, A Barla arXiv preprint arXiv:1612.00615, 2016 | 1 | 2016 |
| Predicting multiple sclerosis disease course with patient centred outcomes (PCOs): a machine learning approach G Brichetto, S Fiorini, M Ponzio, A Barla, A Verri, A Tacchino ECTRIMS 2016, London (UK), 2016 | 1 | 2016 |
| Improving disease course detection in multiple sclerosis: an alternative patient-reported outcomes-based strategy G Brichetto, S Fiorini, A Tacchino, P Michela, A Barla, A Verri MULTIPLE SCLEROSIS 21, 513-514, 2015 | 1 | 2015 |
| Automatic generation of Retinal Fundus Image Phantoms: non-vascular regions S Fiorini | 1 | 2014 |
| Paths of graduates from the University of Genoa (1990-2016) A Barla, S Fiorini, A Licaj, A Vacanti, A Vian IMG2019. International and Interdisciplinary Conference on Images and …, 2019 | | 2019 |
| Switching from Glargine to Degludec is not associated with an overt change in glucose control in a cohort of patients with type 1 diabetes: a CGM analysis LA Bonabello, D Maggi, S Fiorini, V Tozzo, R Cordera Acta Diabetologica 55 (6), 637-639, 2018 | | 2018 |
| Challenges in biomedical data science: data-driven solutions to clinical questions S Fiorini University of Genoa, 2018 | | 2018 |
| Automatic Generation of Retinal Fundus Image Phantoms: Vascular Regions M De Biasi | | 2014 |
Annalisa BarlaAssociate Professor at Computer Science Department, University of Genoa, ItalyVerified email at unige.it
