Deep learning-based patient re-identification is able to exploit the biometric nature of medical chest X-ray data.

ABSTRACT: With the rise and ever-increasing potential of deep learning techniques in recent years, publicly available medical datasets became a key factor to enable reproducible development of diagnostic algorithms in the medical domain. Medical data contains sensitive patient-related information and is therefore usually anonymized by removing patient identifiers, e.g., patient names before publication. To the best of our knowledge, we are the first to show that a well-trained deep learning system is able to recover the patient identity from chest X-ray data. We demonstrate this using the publicly available large-scale ChestX-ray14 dataset, a collection of 112,120 frontal-view chest X-ray images from 30,805 unique patients. Our verification system is able to identify whether two frontal chest X-ray

SUBMITTER: Packhauser K 

PROVIDER: S-EPMC9434540 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature