ArticleJournal of education and health promotion2022
Developing an artificial neural network for detecting COVID-19 disease.
Article in Journal of education and health promotion, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- AI-Driven Innovation in Skin Kinetics for Transdermal Drug Delivery: Overcoming Barriers and Enhancing Precision.Pharmaceutics · 2025Review
- Prediction of primary Hypertension in Primary Health Care Settings in Coastal Karnataka Using Artificial Neural Network.Current hypertension reviews · 2025Article
- Expanding access to veterinary clinical decision support in resource-limited settings: a scoping review of clinical decision support tools in medicine and antimicrobial stewardship.Frontiers in veterinary science · 2024Article
- A large language model in solving primary healthcare issues: A potential implication for remote healthcare and medical education.Journal of education and health promotion · 2024Article
- Article
- COVID-19 infection inference with graph neural networks.Scientific reports · 2023Article
- Authentication of Covid-19 Vaccines Using Synchronous Fluorescence Spectroscopy.Journal of fluorescence · 2023Article
- Investigating the performance of machine learning algorithms in predicting the survival of COVID-19 patients: A cross section study of Iran.Health science reports · 2023Article
- Diagnostic accuracy of a set of clinical and radiological criteria for screening of COVID-19 using RT-PCR as the reference standard.BMC pulmonary medicine · 2023Article
- Left ventricular hypertrophy detection using electrocardiographic signal.Scientific reports · 2023Article
- Machine learning to analyse omic-data for COVID-19 diagnosis and prognosis.BMC bioinformatics · 2023Article
- Machine learning algorithms for predicting determinants of COVID-19 mortality in South Africa.Frontiers in artificial intelligence · 2023Article
- Clinical decision support system for quality of life among the elderly: an approach using artificial neural network.BMC medical informatics and decision making · 2022Article
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3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundFrom December 2019, atypical pneumonia termed COVID-19 has been increasing exponentially across the world. It poses a great threat and challenge to world health and the economy. Medical specialists face uncertainty in making decisions based on their judgment for COVID-19. Thus, this study aimed to establish an intelligent model based on artificial neural networks (ANNs) for diagnosing COVID-19. MATERIALS AND
methodsUsing a single-center registry, we studied the records of 250 confirmed COVID-19 and 150 negative cases from February 9, 2020, to October 20, 2020. The correlation coefficient technique was used to determine the most significant variables of the ANN model. The variables at
resultsAfter the feature selection process, a total of 18 variables were determined as the most relevant predictors for developing the ANN models. The results indicated that two nested loops' architecture of 9-10-15-2 (10 and 15 neurons used in layer 1 and layer 2, respectively) with the area under the curve of 0.982, the sensitivity of 96.4%, specificity of 90.6%, and accuracy of 94% was introduced as the best configuration model for COVID-19 diagnosis.
conclusionThe proposed ANN-based clinical decision support system could be considered as a suitable computational technique for the frontline practitioner in early detection, effective intervention, and possibly a reduction of mortality in patients with COVID-19.
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