Can Large Language Models Preserve Diagnostic Accuracy Despite Patient Self-Diagnosis and Framing Bias in Hypothetical Upper-Extremity Scenarios?
In this experimental setting, an LLM identified simulated upper extremity conditions regardless of patient self-diagnosis, suggesting limited susceptibility to the anchoring, confirmation, and acquiescence biases known to affect human diagnostic reasoning.