Enhancing AI-Clinician Interaction: Building Trust to Improve Patient Outcomes

Abstract

This research systematically reviews interpretable machine learning (IML) and explainable AI (XAI) in healthcare, proposing a Responsible Clinician-AI Collaboration Framework. It introduces a novel three-level interpretability process and step-by-step roadmap to enhance AI-clinician communication, fostering trust and improving decision-making in clinical decision support systems (CDSS).