2022
DOI: 10.1007/s11063-021-10712-6
|View full text |Cite
|
Sign up to set email alerts
|

Neighborhood Rough Neural Network Approach for COVID-19 Image Classification

Abstract: The rapid spread of the new Coronavirus, COVID-19, causes serious symptoms in humans and can lead to fatality. A COVID-19 infected person can experience a dry cough, muscle pain, headache, fever, sore throat, and mild to moderate respiratory illness, according to a clinical report. A chest X-ray (also known as radiography) or a chest CT scan are more effective imaging techniques for diagnosing lung cancer. Computed Tomography (CT) scan images allow for fast and precise COVID-19 screening. In this paper, a nove… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
4
0

Year Published

2022
2022
2025
2025

Publication Types

Select...
6
2

Relationship

2
6

Authors

Journals

citations
Cited by 9 publications
(4 citation statements)
references
References 35 publications
0
4
0
Order By: Relevance
“…The feature selection algorithms were implemented in ANACONDA. The measurement equations can be described as follows, (Nivetha et al, 2022c): Tables 8,9,10, 11 and 12 describe several "Decision Tree classifiers", "Random Forest Classifier", "Naïve Bayes classifier", "KNN classifier", and "SVM classifiers". In these tables, it can be seen that using the NHGAO, AOA, GA, and Unreduced data approaches in comparison to the unreduced information increases the accuracy of order classification.…”
Section: Resultsmentioning
confidence: 99%
“…The feature selection algorithms were implemented in ANACONDA. The measurement equations can be described as follows, (Nivetha et al, 2022c): Tables 8,9,10, 11 and 12 describe several "Decision Tree classifiers", "Random Forest Classifier", "Naïve Bayes classifier", "KNN classifier", and "SVM classifiers". In these tables, it can be seen that using the NHGAO, AOA, GA, and Unreduced data approaches in comparison to the unreduced information increases the accuracy of order classification.…”
Section: Resultsmentioning
confidence: 99%
“…The "structural similarity index" is a method for determining exactly similar two images seem (Hore et al, 2010, Nivetha, et al, 2022a. In this method, image degradation is considered as the change of perception in structural information.…”
Section: Structural Similarity Index Methodsmentioning
confidence: 99%
“…The limitation of the presented method was the reliability and suitability of the model to the other series of data. Nivetha et al ( 30 ) presented a new classification technique for COVID-19 based on Neighborhood Rough Neural Network Algorithm (NRNN). The presented method performed better than existing algorithms like Backpropagation Neural Network (BNN), Decision Tree, and Naive Bayes Classifiers.…”
Section: Related Studymentioning
confidence: 99%