Ensemble deep honey architecture for COVID-19 prediction using CT scan and chest X-ray images.

ABSTRACT: Recently, the infectious disease COVID-19 remains to have a catastrophic effect on the lives of human beings all over the world. To combat this deadliest disease, it is essential to screen the affected people quickly and least inexpensively. Radiological examination is considered the most feasible step toward attaining this objective; however, chest X-ray (CXR) and computed tomography (CT) are the most easily accessible and inexpensive options. This paper proposes a novel ensemble deep learning-based solution to predict the COVID-19-positive patients using CXR and CT images. The main aim of the proposed model is to provide an effective COVID-19 prediction model with a robust diagnosis and increase the prediction performance. Initially, pre-processing, like image resizing and noise removal,

SUBMITTER: Reddy BB 

PROVIDER: S-EPMC10088783 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature