01/01/2026
Safeguarding Clinical Reasoning: A Defense Framework for Artificial Intelligence in Otolaryngology
Chin-Lung Kuo, MD, PhD
AI is rapidly evolving from a supportive tool into a core component of medical decision making and evidence synthesis, reshaping how clinicians interpret information at the point of care. Yet, while much of medical AI research emphasizes algorithmic performance and explainability, it seldom addresses the more practical question: how should physicians evaluate an AI recommendation in real-world, high-risk situations when fluent outputs can conceal critical errors. This Perspective offers a clinician-centered framework that treats AI outputs as provisional, testable hypotheses rather than definitive conclusions. By guiding users through premise verification, terminological precision, evidence appraisal, and causal analysis, it provides a structured defense against hallucinations, selective reporting, and data poisoning, using otolaryngology as a high-stakes, multimodal model. By placing clinical judgment at the center of AI use, this work shifts the field from passive automation toward safer, more accountable decision support grounded in patient safety.
Article: https://scitemed.com/article/5444/scitemed-aohns-2025-00204
PDF: https://scitemed.com/upload/3714/5444/scitemed.aohns.2025.00204.pdf?t=2211
