Figure 2 : Quantitative image features successfully distinguished histopathology images of lung adenocarcinoma from those of lung squamous cell carcinoma.

From: Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features

Figure 2

(a) ROC curves for classifying the two malignancies in the TCGA test set. Most classifiers achieved AUC>0.7. (b) ROC curves for classifying the two malignancies in the TMA test set. Most classifiers achieved AUC >0.75, indicating that our informatics pipeline was successfully validated in the independent TMA data set. The performance of different classifiers is shown. CIT, conditional inference trees; ROC, receiver operator characteristics.