Addressing Bias and Shortcuts in Clinical AI Models

Exploring the impact of shortcuts and biases in clinical AI models, focusing on the importance of recognizing and mitigating these issues to prevent errors in diagnoses. The chapter highlights the role of visual explanations in helping clinicians identify biased models and discusses the impact of automation bias on decision-making in clinical practice. It also delves into the limitations of explainer models and the necessity for more effective tools to explain AI models in healthcare.