COVID-19 Diagnosis from CT Images with Convolutional Neural Network Optimized by Marine Predator Optimization Algorithm

Biomed Res Int. 2021 Oct 12;2021:5122962. doi: 10.1155/2021/5122962. eCollection 2021.ABSTRACTIn recent years, almost every country in the world has struggled against the spread of Coronavirus Disease 2019. If governments and public health systems do not take action against the spread of the disease, it will have a severe impact on human life. A noteworthy technique to stop this pandemic is diagnosing COVID-19 infected patients and isolating them instantly. The present study proposes a method for the diagnosis of COVID-19 from CT images. The method is a hybrid method based on convolutional neural network which is optimized by a newly introduced metaheuristic, called marine predator optimization algorithm. This optimization method is performed to improve the system accuracy. The method is then implemented on the chest CT scans with the COVID-19-related findings (MosMedData) dataset, and the results are compared with three other methods from the literature to indicate the method's performance. The final results indicate that the proposed method with 98.11% accuracy, 98.13% precision, 98.66% sensitivity, and 97.26% F1 score has the highest performance in all indicators than the compared methods which shows its higher accuracy and reliability.PMID:34651046 | PMC:PMC8510794 | DOI:10.1155/2021/5122962
Source: Biomed Res - Category: Research Authors: Source Type: research