Multi-Label Classification of Thoracic Diseases using Dense Convolutional Network on Chest Radiographs

arXiv:2202.03583v4 Announce Type: replace-cross
Abstract: Traditional methods of identifying pathologies in X-ray images rely heavily on skilled human interpretation and are often time-consuming. The advent of deep learning techniques has enabled the development of automated disease diagnosis systems. Still, the performance of such systems is opaque to end-users and limited to detecting a single pathology. In this paper, we propose a multi-label disease prediction model that allows the detection of more than one pathology at a given test time. We …

abstract arxiv automated classification cs.ai cs.cv cs.lg deep learning deep learning techniques development diagnosis disease disease diagnosis diseases eess.iv human images interpretation network performance ray skilled systems type x-ray