Digital Service Platform for Networked Enterprises Collaboration: A Case Study of the NEMESYS Project. - Francesco Bellini; Fabrizio D'Ascenzo; Iana Dulskaia; Marco Savastano (IESS, 2016)

The antecedents of e-learning adoption within Italian corporate universities: a comparative case study. - Michela Iannotta; C. Meret; Mauro Gatti; Fabrizio D'Ascenzo (EAI Endorsed Trans. e Learn., 2016)

FabLabs as Platforms for Digital Fabrication Services: A Literature Analysis. - Marco Savastano; Francesco Bellini; Fabrizio D'Ascenzo; Eusebio Scornavacca Jr. (IESS, 2017)

Digital Communication Tools and Knowledge Creation Processes for Enriched Intellectual Outcome - Experience of Short-Term E-Learning Courses during Pandemic. - Nadezhda N. Pokrovskaia; Veronika L. Leontyeva; Marianna Yu. Ababkova; Lucio Cappelli; Fabrizio D'Ascenzo (Future Internet, 2021)

Modelling coronary flows: impact of differently measured inflow boundary conditions on vessel-specific computational hemodynamic profiles. - Maurizio Lodi Rizzini; Alessandro Candreva; Claudio Chiastra; Emanuele Gallinoro; Karol Calò; Fabrizio D'Ascenzo; Bernard De Bruyne; Takuya Mizukami; Carlos Collet; Diego Gallo; Umberto Morbiducci (Comput. Methods Programs Biomed., 2022)

Pooling critical datasets with Federated Learning. - Yasir Arfat; Gianluca Mittone; Iacopo Colonnelli; Fabrizio D'Ascenzo; Roberto Esposito; Marco Aldinucci (PDP, 2023)

Modelling blood flow in coronary arteries: Newtonian or shear-thinning non-Newtonian rheology? - Giuseppe De Nisco; Maurizio Lodi Rizzini; Roberto Verardi; Claudio Chiastra; Alessandro Candreva; Gaetano de Ferrari; Fabrizio D'Ascenzo; Diego Gallo; Umberto Morbiducci (Comput. Methods Programs Biomed., 2023)

Coronary Artery Stenosis Assessment in X-Ray Angiography Through Spatio-Temporal Attention for Non-Invasive FFR and iFR Estimation. - Raffaele Mineo; Federica Proietto Salanitri; Giovanni Bellitto; Ovidio De Filippo; Fabrizio D'Ascenzo; Simone Palazzo; Concetto Spampinato (BIOSTEC (1), 2024)

An innovative artificial intelligence-based method to compress complex models into explainable, model-agnostic and reduced decision support systems with application to healthcare (NEAR). - Karim Kassem; Michela Sperti; Andrea Cavallo; Andrea Mario Vergani; Davide Fassino; Monica Moz; Alessandro Liscio; Riccardo Banali; Michael Dahlweid; Luciano Benetti; Francesco Bruno; Guglielmo Gallone; et al. (Artif. Intell. Medicine, 2024)

Detection of subclinical atherosclerosis by image-based deep learning on chest x-ray. - Guglielmo Gallone; Francesco Iodice; Alberto Presta; Davide Tore; Ovidio De Filippo; Michele Visciano; Carlo Alberto Barbano; Alessandro Serafini; Paola Gorrini; Alessandro Bruno; Walter Grosso Marra; James Hughes; et al. (CoRR, 2024)

A Convolutional-Transformer Model for FFR and iFR Assessment From Coronary Angiography. - Raffaele Mineo; Federica Proietto Salanitri; Giovanni Bellitto; Isaak Kavasidis; Ovidio De Filippo; M. Millesimo; Gaetano Maria de Ferrari; Marco Aldinucci; Daniela Giordano; Simone Palazzo; Fabrizio D'Ascenzo; Concetto Spampinato (IEEE Trans. Medical Imaging, 2024)