Abstract
Artificial intelligence (AI) is transforming how clinicians perceive, interpret, and act upon diagnostic information. Yet the step from algorithmic output to informed clinical decision remains complex, requiring not only technical understanding but also critical reflection. This workshop explores how AI can augment human judgment in diagnostic and therapeutic processes, with a particular focus on multimodal data integration—from imaging and sensor signals to clinical and behavioral information.
Participants will gain hands-on experience with an AI-supported diagnostic tool, experimenting with real-world datasets and multimodal sensor inputs. Through guided exercises and group discussions, we will examine how AI-driven insights can inform, challenge, or refine clinical decisions. Beyond demonstrating current capabilities, the workshop will address limitations, transparency, and ethical dimensions of AI-assisted decision-making, as well as the need for what is now called „data literacy“.
By the end of the session, attendees will have developed a practical and conceptual understanding of how AI systems process complex diagnostic information and how clinicians can critically engage with these outputs to improve care quality and patient outcomes.
