Predicting HER2 overexpression in prostate cancer using machine learning: implications for personalized therapy.

Concurrently, univariable logistic regression analysis was performed on preoperative clinical variables within the training set to identify potential predictors, using a liberal significance threshold of p < 0.10 to avoid overlooking marginally significant features ( Table 3 ).

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