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Invited speaker: Enea Parimbelli, PhD
Invited speaker: Enea Parimbelli, PhD
Assistant professor, Department of Electrical, Computer and Biomedical Engineering, University of Pavia
Assistant professor, Department of Electrical, Computer and Biomedical Engineering, University of Pavia
Title: Questioning eXplainable AI as the solution to the implementation challenges of clinical AI
Title: Questioning eXplainable AI as the solution to the implementation challenges of clinical AI
Abstract: In an era where AI applications are advancing at an extraordinary pace, the deployment of AI-based solutions in clinical healthcare remains limited. Numerous barriers have been identified as key obstacles to realizing the potential benefits of AI for improving healthcare effectiveness and efficiency. These include concerns around Fairness, Accountability, Trustworthiness, and economic sustainability/ROI for healthcare organizations.
Abstract: In an era where AI applications are advancing at an extraordinary pace, the deployment of AI-based solutions in clinical healthcare remains limited. Numerous barriers have been identified as key obstacles to realizing the potential benefits of AI for improving healthcare effectiveness and efficiency. These include concerns around Fairness, Accountability, Trustworthiness, and economic sustainability/ROI for healthcare organizations.
Explainable AI (XAI) has emerged as one of the widely promoted responses to these challenges and is increasingly being embedded as a requirement in regulatory frameworks in both the EU and North America. This talk will offer an overview of the current landscape of XAI, with a particular emphasis on healthcare applications, and will critically assess whether XAI can genuinely accelerate the adoption of AI innovations in the high-stakes context of clinical care.
Explainable AI (XAI) has emerged as one of the widely promoted responses to these challenges and is increasingly being embedded as a requirement in regulatory frameworks in both the EU and North America. This talk will offer an overview of the current landscape of XAI, with a particular emphasis on healthcare applications, and will critically assess whether XAI can genuinely accelerate the adoption of AI innovations in the high-stakes context of clinical care.
Bio: Enea Parimbelli is an Assistant Professor of Bioengineering at the University of Pavia and holds an adjunct appointment at the Telfer School of Management at the University of Ottawa, Canada. From June 2025, Enea is also director of the MIAI – Medical Informatics and AI – research unit at IRCCS Fondazione Mondino Neurological Institute in Pavia (IT), coordinating the institute’s digital transition. His research interests revolve around applying Artificial Intelligence methods to the biomedical domain, particularly eXplainable AI, clinical decision support systems, and health informatics.
Enea is a member of the board of directors of the Artificial Intelligence in Medicine Society, Scientific Program Chair of AIME2024, and Chair of the Local Organizing Committee of the upcoming MIE2026. He serves as program committee member of several conferences in the AI domain (AAAI, IJCAI, NIPS, ICML, PKDD). In his free time, Enea enjoys tropical aquarium fish, reading poetry, playing volleyball, and freediving deep waters.
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