An oppositional-Cauchy based GSK evolutionary algorithm with a novel deep ensemble reinforcement learning strategy for COVID-19 diagnosis.

ABSTRACT: A novel coronavirus (COVID-19) has globally attracted attention as a severe respiratory condition. The epidemic has been first tracked in Wuhan, China, and has progressively been expanded in the entire world. The growing expansion of COVID-19 around the globe has made X-ray images crucial for accelerated diagnostics. Therefore, an effective computerized system must be established as a matter of urgency, to facilitate health care professionals in recognizing X-ray images from COVID-19 patients. In this work, we design a novel artificial intelligent-based automated X-ray image analysis framework based on an ensemble of deep optimized convolutional neural networks (CNNs) in order to distinguish coronavirus patients from non-patients. By developing a modified version of gaining-sharing knowled

SUBMITTER: Jalali SMJ 

PROVIDER: S-EPMC8272021 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature