Journal ArticleOpen Access
A Novel Bayesian Optimization-Based Machine Learning Framework for COVID-19 Detection From Inpatient Facility Data
Author Affiliations
Khulna University, Taif University, Quantitative BioSciences, International University of Business Agriculture and Technology, ...
Published InIEEE Access
Year2021
Citations86
Abstract
The whole world faces a pandemic situation due to the deadly virus, namely COVID-19. It takes considerable time to get the virus well-matured to be traced, and during this time, it may be transmitted among other people. To get rid of this unexpected situation, quick identification of COVID-19 patients is required. We have designed and optimized a machine learning-based framework using inpatient's facility data that will give a user-friendly, cost-effective, and time-efficient solution to this pandemic. The proposed framework uses Bayesian optimization to optimize the hyperparameters of the classifier and ADAptive SYNthetic (ADASYN) algorithm to balance the COVID and non-COVID classes of the dataset. Although the proposed technique has been applied to nine state-of-the-art classifiers to show the efficacy, it…
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