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ABSTRACT: Background
Precise T staging is an important prerequisite for the treatment decisions of patients with renal cell carcinoma (RCC). We aimed to predict the pathological T1-3 staging of RCC with an automatic multiclass T staging prediction mode.Methods
We retrospectively enrolled 100 consecutive patients with pathologically proven RCC that was newly diagnosed and untreated from Sun Yat-sen University Cancer Center and randomly split these patients into a training set (70%) and an internal testing set (30%). We enrolled additional 29 patients with pathologically proven RCC from The Third Affiliated Hospital of Shenzhen University as the external testing set. We used the training set data to establish a prediction model for pathological T1-3 staging of RCC and validated the eff
SUBMITTER: Tian L
PROVIDER: S-EPMC10102748 | biostudies-literature | 2023 Apr
REPOSITORIES: biostudies-literature