ABSTRACT
The world is facing the global challenge of COVID-19 pandemics, which is a topic of great concern.It is a contagious disease and infects others very fast.Artificial intelligence (AI) can assist healthcare professionals in assessing disease risks, assisting in diagnosis, prescribing medication, forecasting future well, and may be helpful in the current situation.Designing, a user-friendly Web application-based diagnosis model framework, is more useful in health care.The study focuses on a Web-based model for diagnosing the COVID-19 patients without direct contact with the patient.Chest CT scans have been important for the testing and diagnosing of COVID-19 disease.The Web-based model would take inputs, CT scan images, and users' symptoms and display classification results: NON-COVID-19 or COVID-19 infected. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
The world is facing the global challenge of COVID-19 pandemics, which is a topic of great concern.It is a contagious disease and infects others very fast.Artificial intelligence (AI) can assist healthcare professionals in assessing disease risks, assisting in diagnosis, prescribing medication, forecasting future well, and may be helpful in the current situation.Designing, a user-friendly Web application-based diagnosis model framework, is more useful in health care.The study focuses on a Web-based model for diagnosing the COVID-19 patients without direct contact with the patient.Chest CT scans have been important for the testing and diagnosing of COVID-19 disease.The Web-based model would take inputs, CT scan images, and users’ symptoms and display classification results: NON-COVID-19 or COVID-19 infected. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
Background: Ongoing need of alternative strategies for SARS-CoV-2 detection is undeniable. Self-collected samples without viral transport media (VTM), coupled with simple nucleic acid extraction methods for SARS-CoV-2 PCR are beneficial. Objectives: To evaluate results of SARS-CoV-2 PCR using simple nucleic acid extraction methods from self -collected saliva and oral swabs without VTM. Methods: A cross-sectional single-centre study was conducted on 125 participants (101 SARS-CoV-2 positive cases and 24 controls). PCR was performed following five simple nucleic acid extraction methods on self -collect saliva and oral swabs without VTM and results were compared with gold standard PCR. For saliva, kit-based extraction (SKE), Proteinase K and Heat extraction (SPHE), only Heat extraction (SHE) methods and for dry oral swabs, Proteinase K and Heat extraction (DPHE) and only Heat extraction (DHE) was performed. Results: SARS-CoV-2 was detected in self-collected saliva and oral swabs. 93.07% were correctly classified as positive by SKE, 69.31% by SHE, 67.33% by SPHE, 67.33% by DPHE and 55.45% by DHE. Discriminant power of SKE was significantly higher than other methods (p-value < 0.001) with good- fair agreement of alternate extraction methods against gold standard. Conclusion: Combination of self-collected saliva/ oral-swab without VTM and alternative RNA extraction methods offer a simplified, economical substitute strategy for SARS-CoV-2 detection.