Fig. 3: The performance indicators of the model at different levels in both the independent internal and external validation cohort. | Nature Communications

Fig. 3: The performance indicators of the model at different levels in both the independent internal and external validation cohort.

From: Development of deep learning-based narrow-band imaging endocytoscopic classification for predicting colorectal lesions from a retrospective study

Fig. 3

At the image level, we quantitatively perceive the model performance by calculating the receiver operating characteristic (ROC) (a) and confusion matrix (b) of the training and validation cohorts of the model. Further, through the T-SNE method, we perform dimensionality reduction and visualization of the features of the samples. The clustering situation between different classes can be observed (c), and their silhouette scores are quantitatively calculated. The same indicators calculation and visualization are also displayed at the lesion level (d–f).

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