Evaluation of deep learning for COVID‐19 diagnosis: Impact of image dataset organization

Abstract

The experimental results indicate that model may be trained based on differences of the image characteristics between databases and not on lesion features. This shows that evaluation metrics can be influenced by dataset organization, and high metric values would not directly mean the potential for clinical application. These emphasize the importance of suitable dataset organization for applying COVID-19 diagnosis methods to real clinical sites. Radiologists should sufficiently understand about this issue as actual user of these methods.

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