Rivolta Massimo Walter
Fixed-term Research Fellow B
Scientific-Disciplinary Sector
INFO-01/A - Informatics
Scientific-Disciplinary Group/Competition Sector
01/INFO-01 - INFORMATICA
Research fields and competencies
Teaching - Programme courses
Bachelors and masters
A.Y. 2025/2026
A.Y. 2024/2025
A.Y. 2023/2024
A.Y. 2022/2023
A.Y. 2021/2022
A.Y. 2020/2021
Postgraduate programmes
A.Y. 2023/2024
Doctoral programme (PhD)
Research
Publications
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Visiting a loved one in the ICU with the aid of dedicated booklets is associated with reduced separation anxiety in children and adolescents / G. Lamiani, F. Bonazza, M. Maxia, M.W. Rivolta, G. Mistraletti, E. Vegni. - In: CHILD AND ADOLESCENT PSYCHIATRY AND MENTAL HEALTH. - ISSN 1753-2000. - 2025:19(2025 Jun 06). [Epub ahead of print] [10.1186/s13034-025-00906-4]
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Machine Learning approaches for the design of biomechanically compatible bone tissue engineering scaffolds / S. Ibrahimi, L. D’Andrea, D. Gastaldi, M.W. Rivolta, P. Vena. - In: COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING. - ISSN 0045-7825. - 423:(2024), pp. 116842.1-116842.16. [10.1016/j.cma.2024.116842]
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Centrality Measures from Directed Network Mapping Identify Reentries Suggesting Different Mechanisms of Atrial Flutter / D. Coluzzi, M.W. Rivolta, M. Mancini, L. Anna Unger, A. Luik, A. Loewe, R. Sassi - In: Computing in Cardiology[s.l] : IEEE, 2024. - pp. 1-4 (( Intervento presentato al 51. convegno International Computing in Cardiology tenutosi a Karlsruhe nel 2024 [10.22489/cinc.2024.306].
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Minimal Preprocessing of ECG Signals for Deep Learning-Based Biometric Systems / Z. Mizgalewicz, C.R. Cuenca, M.W. Rivolta, R.D. Labati, F. Scotti, V. Piuri, R. Sassi - In: CIVEMSA[s.l] : Institute of Electrical and Electronics Engineers (IEEE), 2024. - ISBN 979-8-3503-2300-9. - pp. 1-5 (( convegno International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications : 14 through 16 June tenutosi a Xi'an (Repubblica Popolare Cinese) nel 2024 [10.1109/civemsa58715.2024.10586617].
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Evidential Deep Learning Model for Atrial Fibrillation Detection from Holter Recordings / M. Moklesur Rahman, M.W. Rivolta, P. Maison Blanche, F. Badilini, R. Sassi - In: Computing in Cardiology[s.l] : IEEE, 2024. - pp. 1-4 (( Intervento presentato al 51. convegno Computing in Cardiology tenutosi a Karlsruhe nel 2024 [10.22489/cinc.2024.384].