Featured Invited Talk - Keynote

Sara Montagna, University of Urbino Carlo Bo, Urbino, ITALY

Bridging AI and Healthcare: Trustworthy and Transparent Diagnostic Solutions with Informed Machine Learning

Abstract

The convergence of Artificial Intelligence and healthcare is not only a trend; it represents a transformative shift that holds the potential to redefine how we understand and improve patient outcomes. As machine learning evolves, leveraging vast datasets to uncover patterns and predictive insights, we find ourselves at a pivotal moment where the challenges of trustworthiness and explainability demand our attention.

In this talk, I will explore the Informed Machine Learning paradigm, specifically discussing the framework of symbolic knowledge integration—where domain expertise is integrated into machine learning frameworks—and symbolic knowledge extraction, which empowers us with interpretable insights from complex models. The goal is to create predictive models that integrate empirical data with established medical guidelines. By fostering this synergy, we can enhance diagnostic accuracy and reduce the prevalence of false negatives, ultimately leading to improved patient care. Accordingly, these approaches are not merely technical enhancements; they signify a paradigm shift toward creating AI systems that are both intelligent and transparent.

About the Speaker

Sara Montagna is an Associate Professor at the University of Urbino Carlo Bo. She earned her Master's degree in Biomedical Engineering in January 2007, graduating with honours (110/110 cum Laude), and completed her PhD in Computer Science in April 2011 at the University of Bologna. Since October 2021, she has been a Research Fellow at the Department of Computer Science and Engineering at the University of Bologna for almost 10 years.

Sara Montagna's scientific work focuses on Medical Informatics, aiming to create innovative computational models and technologies that enhance healthcare services and support connected, inclusive care. Collaborating with various Italian healthcare institutions, she pursues two main goals: (i) to design innovative computing systems in hospital and home care settings, referencing fields like IoT and AI; (ii) to analyse clinical data using Machine Learning and Neuro-symbolic AI algorithms to transform data into actionable insights for improving care outcomes.