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Abstract Background: With the rapid increase in the number of chest CT images, the workload faced by radiologists has increased dramatically. It is undeniable that the future use of artificial intelligence (AI) image-assisted diagnosis system in clinical treatment is a major trend in medical development. Therefore, in order to explore the value and diagnostic accuracy of the current AI system in clinical application, we aims to compare the detection and differentiation of benign and malignant pulmonary nodules between AI system and physicians, so as to provide a theoretical basis for clinical application. Methods:Our study encompassed a cohort of 23,336 patients who underwent chest low-dose spiral CT (LDCT) screening for lung cancer at the Health Management Center of West China Hospital. We conducted a comparative analysis between AI-assisted reading and manual interpretation, focusing on the detection and differentiation of benign and malignant pulmonary nodules. Results: The AI-assisted reading exhibited a significantly higher screening positive rate and probability of diagnosing malignant pulmonary nodules compared to manual interpretation (both P Conclusions: Our findings underscore the superior screening positive rate and lung cancer detection rate achieved through AI-assisted reading compared to manual interpretation. Thus, AI exhibits considerable potential as an adjunctive tool in lung cancer screening within clinical practice settings.
Wu et al. (Fri,) studied this question.
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