Explainability in AI-Driven Medical Diagnostics
Adina Magda Florea
National University of Science and Technology “Politehnica” Bucharest, Romania
ABSTRACT
As artificial intelligence becomes increasingly integrated into medical diagnostics, ensuring transparency and trust in AI-driven decisions is crucial. This talk explores the challenges and advancements in explainability for AI models analyzing medical images. We will discuss methods for interpreting AI predictions, the role of explainability in clinical decision-making, and strategies to bridge the gap between AI systems and healthcare professionals. By enhancing the interpretability of AI diagnostics, we can improve physician confidence, patient trust, and the overall reliability of AI-assisted medical imaging.
SHORT BIO
Adina Magda Florea is Professor at the Department of Computer Science of the National University of Science and Technology POLITEHNICA Bucharest and Director of the Center of Excellence in Artificial Intelligence of the university. Her research interests are in multi-agent systems, machine learning, ambient intelligence, social robots, and human-robot interaction. She is Senior Member of IEEE, Senior Member of ACM, founding member and President of Romanian Association for Artificial Intelligence, and President of the “Réseau de Recherche Francophone sur l’Intelligence Artificielle (RéFIA).