Enea Parimbelli

Biography

Enea is tenure-track assistant professor (RTDb) at the Department of Industrial and Information Engineering, University of Pavia, where he earned his MSc in Computer Engineering in 2011 and a PhD in Bioengineering and Bioinformatics in 2016. Since June 2025, he also serves as Chief Health AI Officer (CHAIO) and Director of the MIAI – Medical Informatics and AI – research unit at the IRCCS Fondazione Casimiro Mondino.

His research focuses on Artificial Intelligence in medicine and medical informatics, particularly in decision support systems, explainable AI, and generative AI for unstructured biomedical data (e.g., text, signals, and images).

Enea teaches the course “Fundamentals of Telemedicine” in the MSc program in Bioengineering at the University of Pavia, as well as “Medical Informatics” in the second-level Master’s program in Medicine and Surgery MEET – Medicine Enhanced by Engineering Technologies.

see Google Scholar for an updated list of publications

Publications

Pe, S. Famiglini, L., et al.

Alternative Strategies to Generate Class Activation Maps Supporting AI-based Advice in Vertebral Fracture Detection in X-ray Images

Published in: MissingFormLabel Methods of Information in Medicine

Nicora, Pe, Santangelo, et al.

Systematic review of AI/ML applications in multi-domain robotic rehabilitation: trends, gaps, and future directions

Published in: Journal of NeuroEngineering and Rehabilitation

Nicora, Parimbelli, Quaglini et al.

Healthcare practitioners and robotic-assisted rehabilitation: understanding needs and barriers

Published in: Journal of NeuroEngineering and Rehabilitation

Peracchio, Nicora, Parimbelli, Buonocore, Dagliati, Bellazzi et al

RelAI: an automated approach to judge pointwise ML prediction reliability

Published in: International Journal of Medical Informatics

Cabitza, Parimbelli

Let XAI generate reliability metadata, not medical explanations

Published in: Computer Methods and Programs in Biomedicine

Samuele Pe, Arianna Dagliati, Enea Parimbelli, Bruna Maria Vittoria Guerra, Stefania Sozzi, Riccardo Bellazzi, Giovanna Nicora

How improper dataset split hinders model generalizability: a systematic comparison in Human activity recognition and exercise evaluation tasks