Mobile Diagnosis of COVID-19 by Biogeography-based Optimization-guided CNN

Since 2019, COVID-19 has profoundly impacted human health around the world. COVID-19 is extremely contagious, so fast automated diagnosis is necessary. In the field of COVID-19 detection, there are many studies based on convolutional neural networks (CNN). This article introduces the Biogeography-based Optimization (BBO) algorithm to tune three hyperparameters of CNN: β_1 for calculating the exponential decay rate of the past gradient, β_2 for calculating the exponential decay rate of the square of the past gradient and the learning rate α . A mobile COVID-19 diagnosis application based on BBO-CNN is developed. The sensitivity of BBO-CNN is 94.46