فهرست نشریات علمی دسترسی آزاد ایران

Background: Artificial intelligence (AI) systems can improve pulmonary nodule detection, but there is concern that prolonged reliance on AI may alter visual search behavior and affect radiologists’ independent interpretive performance when AI support is withdrawn. Objectives: The objective of this study is to evaluate phase-associated changes in pulmonary nodule detection rate after discontinuation of routine AI assistance. Results: The pulmonary nodule detection rate decreased from 37.8% (370/980) in phase I to 26.5% (260/980) in phase II and then increased to 43.2% (423/980) in phase III (overall P < 0.001). In a generalized estimating equation (GEE) model, using phase I as the reference, the adjusted odds of pulmonary nodule detection were significantly lower in phase II [adjusted odds ratio (aOR) 0.595, 95% confidence interval (CI) 0.530 - 0.667; P < 0.001] and significantly higher in phase III (aOR 1.253, 95% CI 1.123 - 1.398; P < 0.001). Phase III also showed higher adjusted odds of detection than phase II (aOR 2.106, 95% CI 1.874 - 2.366; P < 0.001). The phase-related difference was mainly driven by nodules with a maximum reported diameter of ≤ 5 mm. Conclusion: Discontinuation of routine AI assistance was associated with a short-term decrease in pulmonary nodule detection rate, particularly for small nodules, followed by recovery after an AI-free washout period. These findings suggest a potential vulnerability window during AI downtime or workflow transitions and highlight the need for resilient clinical workflows and performance monitoring.