Fig. 2
From: RareNet: a deep learning model for rare cancer diagnosis
Performance of RareNet in cancer diagnosis is illustrated through the confusion matrix, which shows the ability of RareNet to distinguish between cancer (positive) and normal (negative) samples. The matrix shows a false negative rate of 5%, meaning that 5% of cancer samples were incorrectly predicted as normal. The false positive rate is 0%, that is, none of normal samples were misclassified as cancer by RareNet.
