Deep Learning, Artificial Intelligence, Image Classification, Medical Imaging, Radiology.
The dataset is randomly split into training (28744 patients, 98637 images), validation (1672 patients, 6351 images), and test (389 patients, 420 images). There is no patient overlap between the sets. 1.3. 14-Pathology Classification In this case, CheXNet outputs a vector t=14 of binary labels