ArticleCureus2026
Evaluation of the Applicability of an Overseas-Trained Artificial Intelligence System for Mammography Interpretation in Japan.
Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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8 authors.
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Abstract
backgroundBreast cancer remains a major public health issue in Japan, and artificial intelligence (AI)-based computer-aided detection (CAD) systems have the potential to enhance diagnostic performance. We conducted a two-phase evaluation of an AI-CAD trained on non-Japanese data: an external validation using Japanese mammography images and a reader study assessing its impact on diagnostic performance.
methodsWe performed an external validation to evaluate the diagnostic performance of a commercial AI-CAD system using full-field digital mammography (FFDM) images obtained from Japanese patients. This study primarily focused on evaluating the standalone diagnostic performance of an AI-CAD system using a validation cohort of 338 Japanese patients. To further assess its practical utility, a supplementary multi-reader study with 40 selected cases was conducted to observe the interaction between radiologists and AI output. The AI-CAD was developed and trained outside Japan. Diagnostic performance was assessed using sensitivity, specificity, and receiver operating characteristic curve analysis.
resultsOn validation data, the AI-CAD achieved a sensitivity of 79%, specificity of 89%, and an area under the curve (AUC) of 0.897 (95% CI 0.860-0.934). In a reader study of 40 cases, their performance improved from an AUC of 0.750 to 0.756 (Breast Imaging Reporting and Data System (BI-RADS); p=0.505) and from 0.750 to 0.761 (Likelihood of Malignancy; p=0.110) when assisted by AI-CAD.
conclusionsAlthough no statistically significant difference was observed, AI-aided readings yielded AUCs comparable to AI-unaided readings (95% CI overlap); these findings suggest the feasibility of applying an AI‑CAD trained outside Japan to Japanese cases, while larger prospective screening studies are required to establish clinical impact.
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