Abstract:Background
Different pathological subtypes of lung adenocarcinoma lead to different treatment decisions and prognoses, and it is clinically important to distinguish invasive lung adenocarcinoma from preinvasive adenocarcinoma (adenocarcinoma in situ and minimally invasive adenocarcinoma). This study aims to investigate the performance of the deep learning approach on the classification of tumor invasiveness and compare it with the performances of currently available approaches.
Methods
In this study, we prop… Show more
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