A novel classifier architecture based on deep neural network for COVID-19 detection using laboratory findings

Abstract

Unfortunately, Coronavirus disease 2019 (COVID-19) is spreading rapidly all over the world. Along with causing many deaths, it has substantially affected the social life, economics, and infrastructure worldwide in a negative manner. Therefore, it is very important to be able to diagnose the COVID-19 quickly and correctly. In this study, a new feature group based on laboratory findings was obtained considering ethnical and genetic differences for interpretation of blood data. Then, using this feature group, a new hybrid classifier architecture based on deep learning was designed and COVID-19 detection was made. Classification performance indicators were obtained as accuracy of 94.95%, F1-score of 94.98%, precision of 94.98%, recall of 94.98% and AUC of 100%. Achieved results were compared with those of the deep learning classifiers suggested in literature. According to these results, proposed method shows superior performance and can provide more convenience and precision to experts for diagnosis of COVID-19 disease.

Developing an artificial neural network for detecting COVID-19 disease

“…Some studies[ 31 32 33 34 35 36 ] showed that the ANN-based prediction models using clinical or laboratory data can be significantly helpful in a timely, effective, and economical diagnosis of the disease. It can discriminate the COVID-19 from other similar conditions with better accuracy compared to traditional approaches.…”

Estimation of COVID-19 patient numbers using artificial neural networks based on air pollutant concentration levels

“…Aabed and Lashin ( 2021 ) designed a fuzzy logic system to predict the effects of the variables covered, on the rate of Covid-19 spread. Apart from these studies, Göreke et al ( 2021 ) designed a new hybrid classifier architecture using deep learning techniques and used it to detect Covid-19 spread. Another innovative study for Covid-19 detection was designed by Noshad et al ( 2021 ).…”

Boosting COVID-19 Image Classification Using MobileNetV3 and Aquila Optimizer Algorithm

“…The development of advanced artificial intelligence techniques (AI) allows medical researchers and scientists to develop advanced tools, software, and instruments that can help medical radiologists overcome the problems related to human-based detecting techniques [6]. The last two years have seen a surge in the applications of AI in the diagnosis and forecasting of COVID-19 [7][8][9][10][11][12]. Many approaches have been developed to detect and differentiate between COVID-19 disease and conventional viral pneumonia using chest X-ray and CT images [13].…”