Deep Learning Analysis for COVID-19 Using Neural Network Algorithms

Baskar, V. Vijaya; Sivakumar, V.; Vimal, S.; Vadivel, M.

doi:10.1007/978-981-16-5685-9_30

Cited by 1 publication

(1 citation statement)

References 11 publications

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“…This can be considered a long-term effect of corona infection [10][11][12]. It is known that some of the health effects persist for these people who have had long-term COVID- 19.…”

Section: Introductionmentioning

confidence: 99%

Examination of the Effects of Long-term COVID-19 Impacts on Patients with Neurological Disabilities Using a Neuromachine Learning Model

Vaniprabha¹,

Logeshwaran²,

Kiruthiga³

et al. 2023

BIJNN

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Currently, studies have shown that one in three people infected with coronavirus disease-19 (COVID-19) is likely to have had long-term exposure to COVID-19, known as long-term COVID-19. Clinical studies indicate that many people infected with the severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2) COVID-19 pandemic have long-term COVID-19 exposure. According to the study, it has been said that people with diabetes and obesity, and people who have received organ transplants, are more likely to suffer from this long-term effect of COVID-19. In this article, the effects of long-term COVID-19 exposure on neurological disability patients are analyzed with the help of a neuromachine learning model. The proposed model also shows that this long-term COVID problem does not depend on the factors such as race, age, gender, and socioeconomic status of those people. According to the proposed model, people suffering from long-term COVID problems continue to suffer from physical fatigue and shortness of breath and are regularly monitored and classified as per the proposed instructions. Even after they recover from the disease, various side effects are seen.

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“…This can be considered a long-term effect of corona infection [10][11][12]. It is known that some of the health effects persist for these people who have had long-term COVID- 19.…”

Section: Introductionmentioning

confidence: 99%