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1.
Expert Systems ; : 1, 2022.
Article in English | Academic Search Complete | ID: covidwho-1973621

ABSTRACT

Autism spectrum disorder (ASD) is an umbrella term for a number of neurodevelopmental conditions with many heterogeneous behavioural indications. Recent medical imaging approaches use functional Magnetic Resonance Imaging (fMRI) for human recognition of the various neurological syndromes. However, these traditional techniques are time consuming and expensive. Thus, in this research, an optimization assisted deep learning technique, named Feedback Artificial Virus Optimization (FAVO)‐based deep residual network (DRN), is developed. FAVO‐based DRN is designed to incorporate the Feedback Artificial Tree (FAT) algorithm with Anti Corona Virus Optimization (ACVO). First, Region‐Of‐Interest extraction is carried out using thresholding techniques with nub region extraction completed using the proposed FAVO algorithm. ASD classification is then carried out using a DRN classifier. Evaluation of the proposal uses the ABIDE‐1 and ABIDE‐2 datasets. The developed FAVO algorithm attains better accuracy, sensitivity, and specificity of 0.9214, 0.9365, and 0.9142, respectively, by considering ABIDE‐2 dataset. [ FROM AUTHOR] Copyright of Expert Systems is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

2.
International Conference on Business and Technology , ICBT 2021 ; 495 LNNS:1145-1151, 2023.
Article in English | Scopus | ID: covidwho-1971485

ABSTRACT

The world has been hit with several crises during the last decade and still suffering from emerged Corona Virus pandemic economic crisis. Jordanian firms, like other firms around the world faced a financial crisis due to decrease in consumers’ demand and obstacles with shipping goods around the world. The current study examines the impact of the Jordanian national defense law in providing a financial protection for firms during the pandemic. Also, we study the behavior of consumers and business owners using an online interview. The results show that business owners are more likely to keep using the same prices before the quarantine period and consumers are more likely to have a buying panic, which, in return, have a positive impact on cash flow. In addition, the study proposed an equation that would guide business owners in calculating the shortage of cash flow and liquidity (SCFL) during crisis periods that similar to that of the quarantine period of COVID-19.,The study provides recommendation to that governmental authorities on enactment of more regulations and policies that provide guidance on how to deal future economic crisis which should provide protection for the local economy and assist firms in getting the financial support they need go through future crisis. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

3.
Vet Microbiol ; 272: 109499, 2022 Sep.
Article in English | MEDLINE | ID: covidwho-1971083

ABSTRACT

Respiratory viral infections are among the major causes of disease in poultry. While viral dual infections are known to occur, viral interference in chicken airways is mechanistically hardly understood. The effects of infectious bronchitis virus (IBV) infection on tissue morphology, sialic acid (sia) expression and susceptibility of the chicken trachea for superinfection with IBV or avian influenza virus (AIV) were studied. In vivo, tracheal epithelium of chickens infected with IBV QX showed marked inflammatory cell infiltration and loss of cilia and goblet cells five days post inoculation. Plant lectin staining indicated that sialic acids redistributed from the apical membrane of the ciliated epithelium and the goblet cell cytoplasm to the basement membrane region of the epithelium. After administration of recombinant viral attachment proteins to slides of infected tissue, retained binding of AIV hemagglutinin, absence of binding of the receptor binding domain (RBD) of IBV M41 and partial reduction of IBV QX RBD were observed. Adult chicken trachea rings were used as ex vivo model to study the effects of IBV QX-induced pathological changes and receptor redistribution on secondary viral infection. AIV H9N2 infection after primary IBV infection was delayed; however, final viral loads reached similar levels as in previously uninfected trachea rings. In contrast, IBV M41 superinfection resulted in 1000-fold lower viral titers over the course of 48 h. In conclusion, epithelial changes in the chicken trachea after viral infection coincide with redistribution and likely specific downregulation of viral receptors, with the extend of subsequent viral interference dependent on viral species.


Subject(s)
Coinfection , Coronavirus Infections , Infectious bronchitis virus , Influenza A Virus, H9N2 Subtype , Poultry Diseases , Superinfection , Animals , Chickens , Coinfection/veterinary , Coronavirus Infections/veterinary , Infectious bronchitis virus/physiology , Influenza A Virus, H9N2 Subtype/physiology , Superinfection/veterinary , Trachea
4.
8th International Conference on Artificial Intelligence and Security , ICAIS 2022 ; 1586 CCIS:75-85, 2022.
Article in English | Scopus | ID: covidwho-1971396

ABSTRACT

In recent years, Corona Virus Disease 2019 (COVID-19), as a highly contagious disease worldwide, poses a serious threat to public health. It is necessary to scientifically predict the development of the epidemic and to study and judge the situation of the epidemic. Based on the Susceptible-Exposed-Infectious-Recovered (SEIR) model, this paper divides the population according to infectivity and considers the impact of double groups on the spread of the new coronavirus COVID-19. In the propagation model, important factors such as the incubation period, average healing days, and recovery rate are introduced, and its stability is analyzed and simulated. In the end, the experimental results prove that the model is stable and can achieve the desired expected effect. The research results provide a theoretical basis for the accurate simulation of the spread of the epidemic in the population, and have important research value and practical significance for improving the prevention and control strategy of the epidemic. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

5.
Sci Afr ; 17: e01300, 2022 Sep.
Article in English | MEDLINE | ID: covidwho-1967098

ABSTRACT

This paper presents the first comparative study of emerging stock markets' response to the COVID-19 pandemic with evidence from Ghana and Botswana. Using daily time-series data from March 1, 2020, to September 30, 2021, the study estimates parametric, semi-parametric and non-parametric models, and provides evidence to support the negative effects of the COVID-19 pandemic (i.e., the total number of reported COVID-19 cases and deaths) on the stock market performances of Ghana and Botswana. Interestingly, the study shows that the impact of the pandemic on Ghana's stock market is quantitatively greater than the stock market of Botswana. The study calls for fiscal and monetary policies to help firms on the stock market to survive the shock. Going forward, measures aimed at building a robust stock market to withstand such external shocks are critical.

6.
Med Nov Technol Devices ; 15: 100159, 2022 Sep.
Article in English | MEDLINE | ID: covidwho-1966945

ABSTRACT

The mortality rate of the recent global pandemic corona virus disease 2019 (COVID-19) is currently as high as 7%. The SARS-CoV-2 virus is the culprit behind COVID-19. SARS-CoV-2 is an enveloped single-stranded RNA virus, the genome encodes four types of the structural proteins: S protein, E protein (envelope protein), M protein (matrix protein) and N protein (nucleocapsid protein). In COVID-19, monoclonal antibodies have played a significant role in diagnosis and treatment. This article briefly introduced the development of monoclonal antibodies targeting on S protein and N protein, which represents the main direction of monoclonal antibody drugs used in the diagnosis and treatment of COVID-19. Meanwhile, the traditional Chinese medicine also plays important role in the fight against COVID-19 by regulating human immunity. The article introduced the use of traditional Chinese medicine in fighting against COVID-19.

7.
Adv Eng Softw ; 173: 103212, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-1966271

ABSTRACT

The establishment of fuzzy relations and the fuzzification of time series are the top priorities of the model for predicting fuzzy time series. A lot of literature studied these two aspects to ameliorate the capability of the forecasting model. In this paper, we proposed a new method(FTSOAX) to forecast fuzzy time series derived from the improved seagull optimization algorithm(ISOA) and XGBoost. For increasing the accurateness of the forecasting model in fuzzy time series, ISOA is applied to partition the domain of discourse to get more suitable intervals. We improved the seagull optimization algorithm(SOA) with the help of the Powell algorithm and a random curve action to make SOA have better convergence ability. Using XGBoost to forecast the change of fuzzy membership in order to overcome the disadvantage that fuzzy relation leads to low accuracy. We obtained daily confirmed COVID-19 cases in 7 countries as a dataset to demonstrate the performance of FTSOAX. The results show that FTSOAX is superior to other fuzzy forecasting models in the application of prediction of COVID-19 daily confirmed cases.

8.
Asian Journal of Chemistry ; 34(8):1993-1996, 2022.
Article in English | Scopus | ID: covidwho-1964682

ABSTRACT

The impact of repurposing drugs that now in vitro inhibit significant chronic respiratory illness corona virus type 2 was indeed underestimated or ignored during the early phases of the COVID-19 virus. Recent clinical data, however, suggest that remdesivir and favipiravir may hasten to heal, but lopinavir/ritonavir had minimal impact on very ill patients. The interferon appears to be the primary impact of triple therapy with ribavirin, lopinavir and interferon-1b. The role of hydroxychloroquine, marketed as Plaquenil® or chloroquine, marketed as Aralen®, in the treatment and prevention of COVID-19 is presently unknown due to the small sample size research. Anti-cytokine drugs may not benefit persons with mild disease or severe illness. Traditional Chinese medicine (TCM) is commonly used for COVID-19 patients in China and has antiviral and immunomodulatory effects on SARS-CoV-2. This review outlines existing COVID-19 therapeutic options and advocates for clinical trials for children, persons with mild disease and those in the early stages of COVID-19. © 2022 Chemical Publishing Co.. All rights reserved.

9.
12th International Conference on Biomedical Engineering and Technology, ICBET 2022 ; : 44-50, 2022.
Article in English | Scopus | ID: covidwho-1962430

ABSTRACT

The pandemic caused by the coronavirus resulted in health protocols regulations to prevent the disease's spread. The World Health Organization recommended using facemasks as a preliminary measure that governments around the world could use help prevent the outbreak. The study's goal is to implement computer vision for facial detection with faces wearing a face mask. The study aims to: (1) capture facial features of masked faces using a Web Camera;and (2) detect a face with proper face mask orientation using deep neural network and mobile net model. (3) For the system to detect whether a person is appropriately wearing a face mask following IATF and WHO standards. The study only allowed one person to face the camera while wearing Standard Surgical Face Masks and being within eye level of the camera if ambient lighting was available. Face Mask Detection, with the Raspberry Pi, has checked the proper face mask orientation for 50 different individuals. The Confusion Matrix Testing determined the following values: 80 percent for the FMD's Accuracy, 62.5 percent for the FMD's Precision, 71.4 percent for the FMD's Recall, Sensitivity, and True Positive Rate, 66.6 percent for the F1 Score, and 16.6 percent for the False Positive Rate. © 2022 ACM.

10.
J Cosmet Dermatol ; 2022 Jul 22.
Article in English | MEDLINE | ID: covidwho-1956775

ABSTRACT

BACKGROUND: COVID-19 has been linked to a variety of dermatological conditions. OBJECTIVE: To determine the presence of various cutaneous manifestations in patients with COVID-19, also to define their features in relation to the systemic symptoms. METHODS: This research enrolled a total of 1206 lab-confirmed COVID-19 individuals at a tertiary-care hospital in Karachi, Pakistan. Expert dermatologists assessed patients for COVID-related skin conditions. COVID-19 severity was categorized as asymptomatic/mild, moderate, or severe. RESULTS: Of the 102 (85.7%) patients with only one cutaneous sign, 26.5% developed maculopapular/morbiliform/erythematous rash; 14.7% urticaria; 9.85% vesicular/pustular exanthem; 14.7% vascular pattern; 12.7% infections, 7.8% miscellaneous and 9.8% late cutaneous findings A longer-lasting vascular pattern was related with an older age and a fatal COVID-19 outcomes (P: 0.000) compared with mild/moderate disease. Most of the retiform purpura presented exclusively with thromboembolic episodes. The moderate severity was correlated with maculopapular/morbiliform/exanthematous phenotype (P: 0.009), whereas urticaria was attributed to asymptomatic/mild disease (0.001) compared with moderate/severe infection. LIMITATIONS: Single-Center and observational study. CONCLUSION: Vascular lesions were correlated with disastrous COVID-19 outcomes, whereas retiform purpura was linked to adverse outcomes. The maculopapular/morbiliform/erythematous rash was associated with moderate severity, while the urticarial rash was linked to milder course compared with moderate/severe severity infection.

11.
Inform Med Unlocked ; 32: 101025, 2022.
Article in English | MEDLINE | ID: covidwho-1956179

ABSTRACT

A new artificial intelligence (AI) supported T-Ray imaging system designed and implemented for non-invasive and non-ionizing screening for coronavirus-affected patients. The new system has the potential to replace the standard conventional X-Ray based imaging modality of virus detection. This research article reports the development of solid state room temperature terahertz source for thermograph study. Exposure time and radiation energy are optimized through several real-time experiments. During its incubation period, Coronavirus stays within the cell of the upper respiratory tract and its presence often causes an increased level of blood supply to the virus-affected cells/inter-cellular region that results in a localized increase of water content in those cells & tissues in comparison to its neighbouring normal cells. Under THz-radiation exposure, the incident energy gets absorbed more in virus-affected cells/inter-cellular region and gets heated; thus, the sharp temperature gradient is observed in the corresponding thermograph study. Additionally, structural changes in virus-affected zones make a significant contribution in getting better contrast in thermographs. Considering the effectiveness of the Artificial Intelligence (AI) analysis tool in various medical diagnoses, the authors have employed an explainable AI-assisted methodology to correctly identify and mark the affected pulmonary region for the developed imaging technique and thus validate the model. This AI-enabled non-ionizing THz-thermography method is expected to address the voids in early COVID diagnosis, at the onset of infection.

12.
International Journal of Work Organisation and Emotion ; 13(2):172-185, 2022.
Article in English | Scopus | ID: covidwho-1951602

ABSTRACT

The present study aimed to evaluate the effect of mindfulness intervention based on stress reduction in psychological distress and self-efficacy of health industry staff in Russia in 2021 during the COVID-19 pandemic. The statistical population included 600 physicians and nurses working in COVID-19 wards of hospitals in Moscow. Data were collected using standard questionnaires. Data analysis was performed in SPSS. According to the results, mindfulness intervention based on stress reduction improved psychological distress and self-efficacy in nurses of the test group, compared to the control group, during the COVID-19 pandemic (P < 0.05). According to the results, mindfulness treatment based on stress reduction reduced three components of psychological distress, stress (F = 24.03, effect size = 0.78, P < 0.001), anxiety (F = 32.12, effect size = 0.69, P = 0.001), and depression (F = 22.31, effect size = 0.72, P = 0.001) while increasing self-efficacy (F = 44.52, effect size = 0.84, P = 0.001). Copyright © 2022 Inderscience Enterprises Ltd.

13.
J Prev Med Hyg ; 63(1): E19-E26, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1955102

ABSTRACT

Introduction: Secondary bacterial infections have been reported in majority of patients hospitalized with coronavirus disease 2019 (COVID-19). A study of the antimicrobial susceptibility profiles of these bacterial strains revealed that they were multidrug resistant, demonstrating their resistance to at least three classes of antimicrobial agents including beta-lactams, fluoroquinolones and aminoglycosides. Bacterial co-infection remains as an important cause for high mortality in patients hospitalized with COVID-19. Methods: In our study, we conducted a retrospective comparative analysis of bacterial co-infections and the antimicrobial resistance profile of bacterial isolates obtained from inpatients admitted in COVID-19 and non-COVID-19 intensive care units. The goal was to obtain the etiology and antimicrobial resistance of these infections for more accurate use of antimicrobials in clinical settings. This study involved a total of 648 samples collected from 356 COVID-19 positive patients and 292 COVID-19 negative patients admitted in the intensive care unit over a period of six months from May to October 2020. Results: Among the co-infections found, maximum antimicrobial resistance was found in Acinetobacter species followed by Klebsiella species in both the ICU's. Incidence of bacterial co-infection was found to be higher in COVID-19 intensive care patients and most of these isolates were multidrug resistant strains. Conclusion: Therefore, it is important that co-infections should not be underestimated and instead be made part of an integrated plan to limit the global burden of morbidity and mortality during the SARS-CoV-2 pandemic and beyond.


Subject(s)
Bacterial Infections , COVID-19 , Coinfection , Bacteria , Bacterial Infections/drug therapy , Bacterial Infections/epidemiology , COVID-19/epidemiology , Coinfection/drug therapy , Coinfection/epidemiology , Drug Resistance, Multiple, Bacterial , Humans , Intensive Care Units , Microbial Sensitivity Tests , Prevalence , Retrospective Studies , SARS-CoV-2
14.
Cureus ; 14(4): e24461, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1954920

ABSTRACT

Hyaluronic acid dermal fillers are a very popular choice for patients wanting to undergo non-invasive facial rejuvenation. Its prevalence is predicted to continue to rise. We report a case of delayed angioedema and associated urticaria to hyaluronic acid dermal fillers post COVID-19 infection. To our knowledge, this is an unusual case of hypersensitivity reaction of eight-month latency. Although the aetiology warrants further research, the author suggests utilisation of a four-week time window between dermal filler injections and COVID-19 vaccination.

15.
23rd International Symposium on Quality Electronic Design, ISQED 2022 ; 2022-April, 2022.
Article in English | Scopus | ID: covidwho-1948806

ABSTRACT

COVID-19 (Corona Virus Disease 2019) is a pandemic which has been spreading exponentially around the globe. Many countries had adopted stay-at-home or lockdown policies to control its spreading. However, prolonged stay-at-home can cause worse effects like economic crises, unemployment, food scarcity, and mental health problems of individuals. EasyBand2.0 is a wearable personal safety device that helps in social distancing and also helps in safe mobility. Under the IoMT (Internet of Medical Things) framework the wearable EasyBand2.0 device helps in social distancing, it avoids human-to-human contact and helps maintain a safer distance. EasyBand2.0 uses the Low Power BLE technology to sense distance between two user devices and alert them based on the distance and time spent in proximity. Safe mobility of people is also important as travel is resumed in all forms. This paper proposes a software application along with the easy band to further be integrated with a system that works based on GPS (Global Positioning System) or GIS (Geographic Information System) to provide travel logging for contact tracing without exposing personal data. A CARS (Context Aware Recommendation System) based safe zone recommender system is proposed in this paper to aid safe mobility. © 2022 IEEE.

16.
4th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, HORA 2022 ; 2022.
Article in English | Scopus | ID: covidwho-1948764

ABSTRACT

In late 2019, pneumonia epidemics were recorded in Wuhan, China, affecting a large number of individuals. A novel SARS virus was found after a careful investigation of samples from SARS patients. The virus was given the name CORONA because of its coronavirus origin, which was then shortened to COVID-19, which stands for CORONA VIRUS 2019. The World Health Organization declared a pandemic on March 11, 2020. The human brain served as the foundation for civilisation. Neural networks were designed to mimic the human mind's working style in order to profit from their way of thinking. The network of neurons performs similarly to a human neuron. As a result, RBF neural networks have been used to link diagnosis with symptoms because the base-based system is reconciled with the knowledge-based system, which represents symptoms related to the diagnosed disease, and the system becomes suitable for correct disease diagnosis after network training. The current study has two main stages: neuron training, which entails entering the system's parameters and generating random weights ranging from 0 to 1 for each of these parameters, and then applying the RBF neural network function to it and comparing the results with those obtained through COVID-19 health centers. © 2022 IEEE.

17.
Interdiscip Neurosurg ; 29: 101599, 2022 Sep.
Article in English | MEDLINE | ID: covidwho-1945266

ABSTRACT

Background: Initially, novel severe acute respiratory syndrome coronavirus (SARS-CoV-2) was considered primarily a respiratory pathogen. However, with time it has behaved as a virus with the potential to cause multi-system involvement, including neurological manifestations which varies from acute to subacute onset of headache, seizures, a decrease of consciousness, and paralysis. Case description: Two cases of cerebral sinus venous thrombosis in COVID-19 patients were reported, following respiratory disorders, which was triggered by the SARS-CoV-2 infection. The first patient, presented with a decrease in level of consciousness and hemiparesis, was 23 years old female having no history of previous medical co-morbidities. The latter case, 21 years old woman showed less severe presentations of COVID-19 associated with headache, vomiting and papilledema. These two cases marvellously improved with no neurological deficit with aggressive course of anticoagulation. Conclusion: CVST should be suspected in COVID-19 patients presenting with headache, paralysis, aphasia or seizures. The high mortality rate of CVST in COVID-19 infection warrants a high index of suspicion from physicians, and early treatment with anticoagulation should be initiated.

18.
Indian J Otolaryngol Head Neck Surg ; : 1-5, 2021 Jul 08.
Article in English | MEDLINE | ID: covidwho-1943021

ABSTRACT

Covid 19 infection can result in various opportunistic infections. Altered immune response, associated comorbid conditions like diabetes, prolonged steroid and broad spectrum antibiotics usage with ICU interventions lead to increased chance of such superadded infections in covid 19 patients. Here we report a case of 31 year old male with covid 19 infection who had new onset Diabetes Mellitus, developed severe acute fulminant Mucormycosis during the treatment for covid 19 infection. He presented with severe headache, nasal obstruction and discharge, bilateral ophthalmoplegia and blindness with Cavernous Sinus Thrombosis. Patient underwent aggressive surgical debridement with frontal craniectomy, maxillectomy and right orbital evisceration and left endoscopic orbital decompression and judicious efforts to revert back the immunocompromised status with high dose of Liposomal amphotericin. Post operatively patient developed right temporal lobe abscess which was drained through Endonasal Endoscopic Trans Cavernous drainage of Temporal Lobe Abscess. Patient is in 2 months follow up, with bilateral blindness and tolerating oral feeds with improved left eye ophthalmoplegia. It is imperative to note that the rising trend of mucormycosis is there in Covid 19 infections and it should be dealt with high index of suspicion in high risk patients and early aggressive treatment can save the patient as the survival rate is not high in such infections.

19.
View (Beijing) ; : 20210020, 2022 Jul 20.
Article in English | MEDLINE | ID: covidwho-1935738

ABSTRACT

The pandemic respiratory disease COVID-19 has spread over the globe within a small span of time. Generally, there are two important points are being highlighted and considered towards the successful diagnosis and treatment process. The first point includes the reduction of the rate of infections and the next one is the decrease of the death rate. The major threat to public health globally progresses due to the absence of effective medication and widely accepted immunization for the COVID-19. Whereas, understanding of host susceptibility, clinical features, adaptation of COVID-19 to new environments, asymptomatic infection is difficult and challenging. Therefore, a rapid and an exact determination of pathogenic viruses play an important role in deciding treatments and preventing pandemic to save the people's lives. It is urgent to fix a standardized diagnostic approach for detecting the COVID-19. Here, this systematic review describes all the current approaches using for screening and diagnosing the COVID-19 infectious patient. The renaissance in pathogen due to host adaptability and new region, facing creates several obstacles in diagnosis, drug, and vaccine development process. The study shows that adaptation of accurate and affordable diagnostic tools based on candidate biomarkers using sensor and digital medicine technology can deliver effective diagnosis services at the mass level. Better prospects of public health management rely on diagnosis with high specificity and cost-effective manner along with multidisciplinary research, specific policy, and technology adaptation. The proposed healthcare model with defined road map represents effective prognosis system.

20.
Studies in Big Data ; 109:79-113, 2022.
Article in English | Scopus | ID: covidwho-1941431

ABSTRACT

Recent Corona Virus Disease (COVID) outbreak, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV2), has been posing a big threat to global health since December 2019. In response, research community from all over the world has shifted all their efforts to contribute in this global war by providing crucial solutions. Various computer vision (CV) technologies along with other artificial intelligence (AI) subsets have significant potential to fight in frontline of this turbulent war. Normally radiologists and other clinicians are using reverse transcript polymerase chain reaction (RT-PCR) for diagnosing COVID-19, which requires strict examination environment and a set of resources. Further, this method is also prone to false negative errors. One of the potential solutions for effective and fast screening of doubtful cases is the intervention of computer vision-based support decision systems in healthcare. CT-scans, X-rays and ultrasound images are being widely used for detection, segmentation and classification of COVID-1. Computer vision is using these modalities and is providing the fast, optimal diagnosis at the early-stage controlling mortality rate. Computer vision-based surveillance technologies are also being used for monitoring physical distance, detecting people with or without face masks, screening infected persons, measuring their temperature, tracing body movements and detecting hand washing. In addition to these, it is also assisting in production of vaccine and contributing in administrative tasks and clinical management. This chapter presents an extensive study of some computer vision-based technologies for detection, diagnosis, prediction and prevention of COVID. Our main goal here is to draw a bigger picture and provide the role of computer vision in fight against COVID-19 pandemic. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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