Evolutionary warning system for COVID-19 severity: Colony predation algorithm enhanced extreme learning machine. (September 2021) - Shi, Beibei; Ye, Hua; Zheng, Long; Lyu, Juncheng; Chen, Cheng; Heidari, Ali Asghar; Hu, Zhongyi; Chen, Huiling; Wu, Peiliang
Abstract: Coronavirus Disease 2019 (COVID-19) was distributed globally at the end of December 2019 due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Early diagnosis and successful COVID-19 assessment are missing, clinical care is ineffective, and deaths are high. In this study, we investigate whether the level of biochemical indicators helps to discriminate and classify the severity of the COVID-19 using the machine learning method. This research creates an efficient intelligence method for the diagnosis of COVID-19 from the perspective of biochemical indexes. The framework is proposed by integrating an enhanced new stochastic called the colony predation algorithm (CPA) with a kernel extreme learning machine (KELM), abbreviated as ECPA-KELM. The core feature of the approach is the ECPA algorithm which incorporates the two main operators that have been abstained from the grey wolf optimizer and moth-flame optimizer to improve and restore the CPA research functions and are simultaneously used to optimize the parameters and to select features for KELM. The ECPA output is checked thoroughly using IEEE CEC2017 benchmark to verify the capacity of the proposed methodology. Finally, in the diagnosis of COVID-19 using biochemical indexes, the designed ECPA-KELM model and other competing KELM models based on other optimization are used. Checking statistical results will display improved predictive properties for all metrics and higher stability. ECPA-KELM can also be used to discriminate and classify the severity of the COVID-19 as a possible computer-aided method and provide effective early warning for the treatment and diagnosis of COVID-19. Highlights: The ECPA-KELM is designed to diagnose COVID-19 from the perspective of biochemical indicators. Performance of the CPA is enhanced special operators from other algorithms. Property of the ECPA is verified on CEC2017 optimization tasks. ECPA can successfully solve KELM's parameter optimization and feature selection simultaneously. ECPA-KELM may be treated as tool for diagnosing COVID-19 from the perspective of biochemical indicators.