  Recent research demonstrates that deep learning models are capable of
precisely extracting bio-information (e.g. race, gender and age) from patients'
Chest X-Rays (CXRs). In this paper, we further show that deep learning models
are also surprisingly accurate at recognition, i.e., distinguishing CXRs
belonging to the same patient from those belonging to different patients. These
findings suggest potential privacy considerations that the medical imaging
community should consider with the proliferation of large public CXR databases.
