Figure 3. Baseline Diagnostic Accuracy Without AI Models and Percentage Point Differences in Accuracy Across Clinical Vignette Settings.

Baseline indicates diagnostic accuracy of heart failure, pneumonia, and chronic obstructive pulmonary disease (COPD) when shown clinical vignettes of patients with acute respiratory failure without AI model input; standard model, diagnostic accuracy when shown clinical vignettes and standard AI model diagnostic predictions about whether the patient has heart failure, pneumonia, and/or COPD; standard model plus explanations, diagnostic accuracy when shown standard AI predictions and an image-based AI explanation of the model’s reasoning for making a prediction within vignettes; systematically biased model, diagnostic accuracy when shown systematically biased AI predictions of low accuracy within vignettes; systematically biased model plus explanations, diagnostic accuracy when shown biased model predictions and explanations within vignettes; and clinical consultation, diagnostic accuracy when provided a short narrative describing the rational for the correct diagnosis within the vignette.

Subgroup analysis included diagnostic accuracy specific to heart failure, pneumonia, and COPD; clinician profession, including 142 nurse practitioners or physician assistants, and 274 physicians; prior clinical decision–support interaction, including 132 participants who had prior experience interacting with clinical decision support systems and 286 who did not. Diagnostic accuracy and percentage point differences in accuracy were determined by calculating predictive margins and contrasts across vignette settings after fitting a cross-classified generalized random effects model of diagnostic accuracy.