IRIS

BERNARDINI, MICHELE

BERNARDINI, MICHELE  

Dipartimento Ingegneria dell'Informazione  

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Risultati 1 - 20 di 20 (tempo di esecuzione: 0.02 secondi).
Titolo Data di pubblicazione Autore(i) File
A clinical decision support system for chronic venous insufficiency 1-gen-2017 Calamanti, Chiara; Cenci, Annalisa; Bernardini, Michele; Frontoni, Emanuele; Zingaretti, Primo
A Clinical Decision Support System to Stratify the Temporal Risk of Diabetic Retinopathy 1-gen-2021 Bernardini, M.; Romeo, L.; Mancini, A.; Frontoni, E.
A Cloud-Based Healthcare Infrastructure for Neonatal Intensive-Care Units 1-gen-2019 Migliorelli, Lucia; Cenci, Annalisa; Bernardini, Michele; Romeo, Luca; Moccia, Sara; Zingaretti, Primo
A Decision Support System for Diabetes Chronic Care Models based on General Practitioner engagement and EHR data sharing 1-gen-2020 Frontoni, Emanuele; Romeo, Luca; Bernardini, Michele; Moccia, Sara; Migliorelli, Lucia; Paolanti, Marina; Ferri, Alessandro; Misericordia, Paolo; Mancini, Adriano; Zingaretti, Primo
A novel missing data imputation approach based on clinical conditional Generative Adversarial Networks applied to EHR datasets 1-gen-2023 Bernardini, Michele; Doinychko, Anastasiia; Romeo, Luca; Frontoni, Emanuele; Amini, Massih-Reza
A Semi-Supervised Multi-Task Learning Approach for Predicting Short-Term Kidney Disease Evolution 1-gen-2021 Bernardini, M.; Romeo, L.; Frontoni, E.; Amini, M.
A sequential deep learning application for recognising human activities in smart homes 1-gen-2019 Liciotti, D.; Bernardini, M.; Romeo, L.; Frontoni, E.
An agent-based WCET analysis for top-view person re-identification 1-gen-2018 Paolanti, M.; Placidi, V.; Bernardini, M.; Felicetti, A.; Pietrini, R.; Frontoni, E.
Augmented microscopy for DNA damage quantification: A machine learning tool for environmental, medical and health sciences 1-gen-2019 Bernardini, M.; Ferri, A.; Migliorelli, L.; Moccia, S.; Romeo, L.; Silvestri, S.; Tiano, L.; Mancini, A.
Cyber Physical Systems for Industry 4.0: Towards Real Time Virtual Reality in Smart Manufacturing 1-gen-2018 Frontoni, Emanuele; Loncarski, Jelena; Pierdicca, Roberto; Bernardini, Michele; Sasso, Michele
Development of an automatic procedure to mechanically characterize soft tissue materials 1-gen-2016 Innocenti, Bernardo; Lambert, Pierre; Larrieu, Jean Charles; Pianigiani, Silvia; Paolanti, Marina; Bernardini, Michele; Cenci, Annalisa; Frontoni, Emanuele
Discovering the Type 2 Diabetes in Electronic Health Records using the Sparse Balanced Support Vector Machine 1-gen-2019 Bernardini, Michele; Romeo, Luca; Misericordia, Paolo; Frontoni, Emanuele
Early temporal prediction of Type 2 Diabetes Risk Condition from a General Practitioner Electronic Health Record: A Multiple Instance Boosting Approach 1-gen-2020 Bernardini, M.; Morettini, M.; Romeo, L.; Frontoni, E.; Burattini, L.
Machine Learning approaches in Predictive Medicine using Electronic Health Records data 26-mag-2021 Bernardini, Michele
Machine learning using the extreme gradient boosting (XGBoost) algorithm predicts 5-day delta of SOFA score at ICU admission in COVID-19 patients 1-gen-2021 Montomoli, Jonathan; Romeo, Luca; Moccia, Sara; Bernardini, Michele; Migliorelli, Lucia; Berardini, Daniele; Donati, Abele; Carsetti, Andrea; Bocci, Maria Grazia; Wendel Garcia, Pedro David; Fumeaux, Thierry; Guerci, Philippe; Schüpbach, Reto Andreas; Ince, Can; Frontoni, Emanuele; Hilty, Matthias Peter; Alfaro-Farias, Mario; Vizmanos-Lamotte, Gerardo; Tschoellitsch, Thomas; Meier, Jens; Aguirre-Bermeo, Hernán; Apolo, Janina; Martínez, Alberto; Jurkolow, Geoffrey; Delahaye, Gauthier; Novy, Emmanuel; Losser, Marie-Reine; Wengenmayer, Tobias; Rilinger, Jonathan; Staudacher, Dawid L.; David, Sascha; Welte, Tobias; Stahl, Klaus; Pavlos”, “Agios; Aslanidis, Theodoros; Korsos, Anita; Babik, Barna; Nikandish, Reza; Rezoagli, Emanuele; Giacomini, Matteo; Nova, Alice; Fogagnolo, Alberto; Spadaro, Savino; Ceriani, Roberto; Murrone, Martina; Wu, Maddalena A.; Cogliati, Chiara; Colombo, Riccardo; Catena, Emanuele; Turrini, Fabrizio; Simonini, Maria Sole; Fabbri, Silvia; Potalivo, Antonella; Facondini, Francesca; Gangitano, Gianfilippo; Perin, Tiziana; Grazia Bocci, Maria; Antonelli, Massimo; Gommers, Diederik; Rodríguez-García, Raquel; Gámez-Zapata, Jorge; Taboada-Fraga, Xiana; Castro, Pedro; Tellez, Adrian; Lander-Azcona, Arantxa; Escós-Orta, Jesús; Martín-Delgado, Maria C.; Algaba-Calderon, Angela; Franch-Llasat, Diego; Roche-Campo, Ferran; Lozano-Gómez, Herminia; Zalba-Etayo, Begoña; Michot, Marc P.; Klarer, Alexander; Ensner, Rolf; Schott, Peter; Urech, Severin; Zellweger, Nuria; Merki, Lukas; Lambert, Adriana; Laube, Marcus; Jeitziner, Marie M.; Jenni-Moser, Beatrice; Wiegand, Jan; Yuen, Bernd; Lienhardt-Nobbe, Barbara; Westphalen, Andrea; Salomon, Petra; Drvaric, Iris; Hillgaertner, Frank; Sieber, Marianne; Dullenkopf, Alexander; Petersen, Lina; Chau, Ivan; Ksouri, Hatem; Sridharan, Govind Oliver; Cereghetti, Sara; Boroli, Filippo; Pugin, Jerome; Grazioli, Serge; Rimensberger, Peter C.; Bürkle, Christian; Marrel, Julien; Brenni, Mirko; Fleisch, Isabelle; Lavanchy, Jerome; Perez, Marie-Helene; Ramelet, Anne-Sylvie; Weber, Anja Baltussen; Gerecke, Peter; Christ, Andreas; Ceruti, Samuele; Glotta, Andrea; Marquardt, Katharina; Shaikh, Karim; Hübner, Tobias; Neff, Thomas; Redecker, Hermann; Moret-Bochatay, Mallory; Bentrup, FriederikeMeyer zu; Studhalter, Michael; Stephan, Michael; Brem, Jan; Gehring, Nadine; Selz, Daniela; Naon, Didier; Kleger, Gian-Reto; Pietsch, Urs; Filipovic, Miodrag; Ristic, Anette; Sepulcri, Michael; Heise, Antje; Franchitti Laurent, Marilene; Laurent, Jean-Christophe; Wendel Garcia, Pedro D.; Schuepbach, Reto; Heuberger, Dorothea; Bühler, Philipp; Brugger, Silvio; Fodor, Patricia; Locher, Pascal; Camen, Giovanni; Gaspert, Tomislav; Jovic, Marija; Haberthuer, Christoph; Lussman, Roger F.; Colak, Elif
Machine learning-based approaches to analyse and improve the diagnosis of endothelial dysfunction 1-gen-2018 Calamanti, Chiara; Paolanti, Marina; Romeo, Luca; Bernardini, Michele; Frontoni, Emanuele
Prediction of complications of type 2 Diabetes: A Machine learning approach 1-gen-2022 Nicolucci, Antonio; Romeo, Luca; Bernardini, Michele; Vespasiani, Marco; Rossi, Maria Chiara; Petrelli, Massimiliano; Ceriello, Antonio; Di Bartolo, Paolo; Frontoni, Emanuele; Vespasiani, Giacomo
Towards the Design of a Machine Learning-based Consumer Healthcare Platform powered by Electronic Health Records and measurement of Lifestyle through Smartphone Data 1-gen-2019 Ferri, A.; Rosati, R.; Bernardini, M.; Gabrielli, L.; Casaccia, S.; Romeo, L.; Monteriu, A.; Frontoni, E.
Towards the Design of a Machine Learning-based Consumer Healthcare Platform powered by Electronic Health Records and measurement of Lifestyle through Smartphone Data 1-gen-2019 Ferri, A.; Rosati, R.; Bernardini, M.; Gabrielli, L.; Casaccia, S.; Romeo, L.; Monteriu, A.; Frontoni, E.
TyG-er: An ensemble Regression Forest approach for identification of clinical factors related to insulin resistance condition using Electronic Health Records 1-gen-2019 Bernardini, M.; Morettini, M.; Romeo, L.; Frontoni, E.; Burattini, L.