RETRACTED ARTICLE: Feature selection for diagnose coronavirus (COVID-19) disease by neural network and Caledonian crow learning algorithm

Abstract

In this study, feature selection methods based on the new Caledonian crow learning algorithm has been introduced. In the proposed algorithms, in the first stage, the best features related to COVID-19 disease are selected by the crow learning algorithm. Coronavirus (COVIDE-19) disease using as training input to the artificial neural network. Experiments on the COVID-19 disease dataset in a Brazilian hospital show that the crow learning algorithm reduces the feature selection objective function by iteration. Decreasing the feature selection function is due to reducing the error of classifying infected people as healthy and reducing the number of features. The experimental results show that the accuracy, sensitivity, precision, and F1 of the proposed method for COVID-19 patients diagnosing are 94.31%, 94.15%, 94.38%, and 94.27%, respectively. The proposed method for identifying COVID-19 patients is more accurate than ANN, CNN, CNNLSTM, CNNRNN, LSTM, and RNN methods.

An Intelligent Feature Selection Approach Based on a Novel Improve Binary Sparrow Search Algorithm for COVID-19 Classification

“…Authors in [27] proposed a method based on mixing the algorithm of PSO with the butterfly optimization algorithm as a search methodology for feature selection from a COVID-19 dataset. The new crow learning algorithm has been introduced in this study [28], which uses feature selection methods as its first stage to identify the best attributes associated with COVID-19 disease. In this article [29], a novel hyper learning binary dragonfly algorithm is proposed to identify the best subset of features for a particular classification problem.…”

خوارزميات ذکاء السرب لتحسين في تشخيص الأمراض: مسح

“…Medical data and patient records are used to uncover hidden patterns in disease diagnosis. Data mining and machine learning are used to retrieve the hidden knowledge within the data [2]. The prediction of an outcome based on historical data is one widely used machine learning application [1].…”

“…One of the most important applications of machine learning is in the creation of disease regression models and categorization. [2]. Also, machine learning is used in many regions, including finance, retail, healthcare, and social data [4].…”

Identification of Pulmonary Hypertension Animal Models Using a New Evolutionary Machine Learning Framework Based on Blood Routine Indicators

“…Pashaei et al [ 17 ] proposed a chimpanzee optimization-based feature selection method for biomedical data classification wrapper. Alsaeedi et al [ 18 ] introduced a feature selection method based on the new caledonian crow learning algorithm to identify whether a population is infected with COVID-19. Lamba et al [ 19 ] proposed a hybrid speech signal-based Parkinson’s disease diagnosis system for early diagnosing Parkinson's disease by combining several feature selection methods and classification algorithms.…”