Region-specific Risk Quantification for Interpretable Prognosis of COVID-19

arXiv:2405.02815v1 Announce Type: new
Abstract: The COVID-19 pandemic has strained global public health, necessitating accurate diagnosis and intervention to control disease spread and reduce mortality rates. This paper introduces an interpretable deep survival prediction model designed specifically for improved understanding and trust in COVID-19 prognosis using chest X-ray (CXR) images. By integrating a large-scale pretrained image encoder, Risk-specific Grad-CAM, and anatomical region detection techniques, our approach produces regional interpretable outcomes that effectively capture essential disease features while focusing on rare …

abstract arxiv control covid covid-19 covid-19 pandemic cs.ai cs.cv diagnosis disease disease spread global health images mortality pandemic paper prediction public public health quantification ray reduce risk survival trust type understanding x-ray