This repository presents an ensemble based transfer learning approach for accurately classifying common thoracic diseases from Chest X-Rays (CXRs)
We use the CheXpert dataset for training and evaluation
The final ensemble consists of the following models
The ensemble weights are found empirically while the disease-wise optimal prediction thresholds are found by maximizing the Younden's J Statistic
The ROC curves for each individual model and the final ensemble are located here
We achieve a mean area under the curve (AUC) of 0.915 on the validation set, that comes close to the SOTA of 0.94 (at the time of writing these models, i.e., May 2020)
