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Federico Del Pup

Showing results (1-10 of 8) with videos related to

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Frontiers in Neuroscience|December 17, 2024
Toward improving reproducibility in neuroimaging deep learning studiesFederico Del Pup, Manfredo Atzori
Journal of Neural Engineering|August 2, 2024
<i>BIDSAlign</i>: a library for automatic merging and preprocessing of multiple EEG repositoriesAndrea Zanola, Federico Del Pup, Camillo Porcaro, et al.
Journal of Neural Engineering|August 2, 2025
xEEGNet: towards explainable AI in EEG dementia classificationAndrea Zanola, Louis Fabrice Tshimanga, Federico Del Pup, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society|March 3, 2025
The More, the Better? Evaluating the Role of EEG Preprocessing for Deep Learning ApplicationsFederico Del Pup, Andrea Zanola, Louis Fabrice Tshimanga, et al.
Computers in Biology and Medicine|July 2, 2025
The role of data partitioning on the performance of EEG-based deep learning models in supervised cross-subject analysis: A preliminary studyFederico Del Pup, Andrea Zanola, Louis Fabrice Tshimanga, et al.
Neuroimage|December 9, 2025
Quantitative neuroimaging meets normative modelling: the last mile for precision medicine applicationsLucia Maccioni, Alessio Giacomel, Marco Pinamonti, et al.
Research Square|May 5, 2025
A global effort to benchmark predictive models and reveal mechanistic diversity in long-term stroke outcomesAnna Matsulevits, Pedro Alves, Manfredo Atzori, et al.
Biorxiv : the Preprint Server for Biology|October 28, 2024
A global effort to benchmark predictive models and reveal mechanistic diversity in long-term stroke outcomesAnna Matsulevits, Pedro Alvez, Manfredo Atzori, et al.
Pageof 1

Showing results (1-10 of 8) with videos related to

Sort By:
Pageof 1
Frontiers in Neuroscience|December 17, 2024
Toward improving reproducibility in neuroimaging deep learning studiesFederico Del Pup, Manfredo Atzori
Journal of Neural Engineering|August 2, 2024
<i>BIDSAlign</i>: a library for automatic merging and preprocessing of multiple EEG repositoriesAndrea Zanola, Federico Del Pup, Camillo Porcaro, et al.
Journal of Neural Engineering|August 2, 2025
xEEGNet: towards explainable AI in EEG dementia classificationAndrea Zanola, Louis Fabrice Tshimanga, Federico Del Pup, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society|March 3, 2025
The More, the Better? Evaluating the Role of EEG Preprocessing for Deep Learning ApplicationsFederico Del Pup, Andrea Zanola, Louis Fabrice Tshimanga, et al.
Computers in Biology and Medicine|July 2, 2025
The role of data partitioning on the performance of EEG-based deep learning models in supervised cross-subject analysis: A preliminary studyFederico Del Pup, Andrea Zanola, Louis Fabrice Tshimanga, et al.
Neuroimage|December 9, 2025
Quantitative neuroimaging meets normative modelling: the last mile for precision medicine applicationsLucia Maccioni, Alessio Giacomel, Marco Pinamonti, et al.
Research Square|May 5, 2025
A global effort to benchmark predictive models and reveal mechanistic diversity in long-term stroke outcomesAnna Matsulevits, Pedro Alves, Manfredo Atzori, et al.
Biorxiv : the Preprint Server for Biology|October 28, 2024
A global effort to benchmark predictive models and reveal mechanistic diversity in long-term stroke outcomesAnna Matsulevits, Pedro Alvez, Manfredo Atzori, et al.
Pageof 1