Alessandro Padovani

According to our database, Alessandro Padovani authored at least 8 papers between 2018 and 2022.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2022

Leveraging process mining for modeling progression trajectories in amyotrophic lateral sclerosis.

Erica Tavazzi, Roberto Gatta, Mauro Vallati, Stefano Cotti Piccinelli, Massimiliano Filosto, Alessandro Padovani, Maurizio Castellano, Barbara Di Camillo

BMC Medical Informatics Decis. Mak., November, 2022

Adopting transfer learning for neuroimaging: a comparative analysis with a custom 3D convolution neural network model.

Amira Soliman, Jose Ramon Chang, Kobra Etminani, Stefan Byttner, Anette Davidsson, Begoña Martínez-Sanchis, Valle Camacho, Matteo Bauckneht, Roxana Stegeran, Marcus Ressner, Marc Agudelo-Cifuentes, Andrea Chincarini, Matthias Brendel, Axel Rominger, Rose Bruffaerts, Rik Vandenberghe, Milica G. Kramberger, Maja Trost, Nicolas Nicastro, Giovanni B. Frisoni, Afina W. Lemstra, Bart N. M. van Berckel, Andrea Pilotto, Alessandro Padovani, Silvia Morbelli, Dag Aarsland, Flavio Nobili, Valentina Garibotto, Miguel Ochoa Figueroa

BMC Medical Informatics Decis. Mak., November, 2022

A study on 3D classical versus GAN-based augmentation for MRI brain image to predict the diagnosis of dementia with Lewy bodies and Alzheimer's disease in a European multi-center study.

Petter Minne, Alvaro Fernandez-Quilez, Dag Aarsland, Daniel Ferreira, Eric Westman, Afina W. Lemstra, Mara Ten Kate, Alessandro Padovani, Irene Rektorova, Laura Bonanni, Flavio Nobili, Milica G. Kramberger, John-Paul Taylor, Jakub Hort, Jón Snædal, Frédéric Blanc, Angelo Antonini, Ketil Oppedal

Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, San Diego, 2022

2021

Gender-Related Vulnerability of Dopaminergic Neural Networks in Parkinson's Disease.

Cecilia Boccalini, Giulia Carli, Andrea Pilotto, Alessandro Padovani, Daniela Perani

Brain Connect., 2021

2020

The reliability of a deep learning model in clinical out-of-distribution MRI data: A multicohort study.

Gustav Mårtensson, Daniel Ferreira, Tobias Granberg, Lena Cavallin, Ketil Oppedal, Alessandro Padovani, Irena Rektorová, Laura Bonanni, Matteo Pardini, Milica G. Kramberger, John-Paul Taylor, Jakub Hort, Jón Snædal, Jaime Kulisevsky, Frédéric Blanc, Angelo Antonini, Patrizia Mecocci, Bruno Vellas, Eric Westman

Medical Image Anal., 2020

2019

An IoT Based Architecture for Enhancing the Effectiveness of Prototype Medical Instruments Applied to Neurodegenerative Disease Diagnosis.

Alessandro Depari, Dhiego Fernandes Carvalho, Paolo Bellagente, Paolo Ferrari, Emiliano Sisinni, Alessandra Flammini, Alessandro Padovani

Sensors, 2019

The reliability of a deep learning model in clinical out-of-distribution MRI data: a multicohort study.

Gustav Mårtensson, Daniel Ferreira, Tobias Granberg, Lena Cavallin, Ketil Oppedal, Alessandro Padovani, Irena Rektorová, Laura Bonanni, Matteo Pardini, Milica G. Kramberger, John-Paul Taylor, Jakub Hort, Jón Snædal, Jaime Kulisevsky, Frédéric Blanc, Angelo Antonini, Patrizia Mecocci, Bruno Vellas, Magda Tsolaki, Iwona Kloszewska, Hilkka Soininen, Simon Lovestone, Andrew Simmons, Dag Aarsland, Eric Westman

CoRR, 2019

2018

Embedded platform-based system for early detection of Alzheimer disease through transcranial magnetic stimulation.

Claudio Crema, Alessandro Depari, Alessandra Flammini, Emiliano Sisinni, Alberto Benussi, Barbara Borroni, Alessandro Padovani

Proceedings of the 2018 IEEE Sensors Applications Symposium, 2018