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An Analysis of Primary Filtering using an Artificial Intelligence Model for Covid-19 Based on Blood Tests

Puneet S

Abstract


It is basic to distinguish people who have previously been contaminated with Coronavirus to control the infection's spread. The highest quality level for Coronavirus ID is rRT-PCR (switch record polymerase chain response) testing, despite the fact that it is a tedious, work escalated manual procedure that is hard to find. We will offer a suitable strategy for Coronavirus starter patient filtration in view of regular blood tests, using computerized reasoning (man-made intelligence) models, here to lessen the quantity of tests. Utilizing Programmed man-made intelligence, our auto-versatile artificial intelligence stage, the most fit artificial intelligence model will be picked.


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References


Wang, W., Xu, Y., Gao, R., Lu, R., Han, K., Wu, G., & Tan, W. (2020). Detection of SARS-CoV-2 in different types of clinical specimens. Jama, 323(18), 1843-1844

Udugama, B., Kadhiresan, P., Kozlowski, H. N., Malekjahani, A., Osborne, M., Li, V. Y., ... & Chan, W.

C. (2020). Diagnosing COVID-19: the disease and tools for detection. ACS nano, 14(4), 3822-3835.

Bukhari, S. U. K., Bukhari, S. S. K., Syed, A., & Shah, S. S. H. (2020). The diagnostic evaluation of Convolutional Neural Network (CNN) for the assessment of chest X-ray of patients infected with COVID-19. MedRxiv.

Zoltan, C. AutomaticAI: A Platform for Automated Evoluptimization of AI Algorithms. Dissertation.

Rasheed, J., Jamil, A., Hameed, A. A., Aftab, U., Aftab, J., Shah, S. A., & Draheim, D. (2020). A survey on artificial intelligence approaches in supporting frontline workers and decision makers for COVID-19 pandemic. Chaos, Solitons & Fractals, 110337.

Kaya, C., Narin, A., Kaya,C., Pamuk,

Z. SARS-CoV-2 or Covid-19 infection detection using X-Ray lung imaging and Deep Convolutional Networks.

Menon, K. D., Raj Jain, A., & Kumar Pareek, D. (2019). Quantitative analysis of student data mining.

Pai H, A., HS, S., Soman, S., Pareek, D., & Kumar, P. (2019). Analysis of causes and effects of longer lead time in software process using FMEA SSRN: https://ssrn.com/abstract=3508574 or http://dx.doi.org/10.2139/ssrn.3508574


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