COVID-19 Detection Based on Lung Ct Scan Using Deep Learning Techniques.

SARS-CoV-2 is a novel virus, responsible for causing the COVID-19 pandemic that has emerged as a pandemic in recent years. Humans are becoming infected with the virus. In 2019, the city of Wuhan reported the first-ever incidence of COVID-19. COVID-19 infected people have symptoms that are related to pneumonia, and the virus affects the body's respiratory organs, making breathing difficult. A real-time reverse transcriptase-polymerase chain reaction (RT-PCR) kit is used to diagnose the disease. Due to a shortage of kits, suspected patients cannot be treated promptly, resulting in disease spread. To develop an alternative, radiologists looked at the changes in radiological imaging, like CT scans, that produce comprehensive pictures of the body of excellent quality. The suspected patient's computed tomography (CT) scan is used to distinguish between a healthy individual and a COVID-19 patient using deep learning algorithms. A lot of deep learning methods have been proposed for COVID-19. The proposed work utilizes CNN architectures like VGG16, DeseNet121, MobileNet, NASNet, Xception, and EfficientNet. The dataset contains 3873 total CT scan images with "COVID" and "Non-COVID." The dataset is divided into train, test, and validation. Accuracies obtained for VGG16 are 97.68%, DenseNet121 is 97.53%, MobileNet is 96.38%, NASNet is 89.51%, Xception is 92.47%, and EfficientNet is 80.19%, respectively. From the obtained analysis, the results show that the VGG16 architecture gives better accuracy compared to other architectures.

Pediatric and geriatric immunity network mobile computational model for COVID-19

PurposeThe computational model proposed in this work uses the data's of COVID-19 cases in India. From the analysis, it can be observed that the proposed immunity model decides the recovery rate of COVID −19 patients;moreover, the recovery rate does not depend on the age of the patients. These analytic models can be used by public health professionals, hospital administrators and epidemiologists for strategic decision-making to enhance health requirements based on various demographic and social factors of those affected by the pandemic. Mobile-based computational model can be used to compute the travel history of the affected people by accessing the near geographical maps of the path traveled.Design/methodology/approachIn this paper, the authors developed a pediatric and geriatric person’s immunity network-based mobile computational model for COVID-19 patients. As the computational model is hard to analyze mathematically, the authors simplified the computational model as general COVID-19 infected people, the computational immunity model. The model proposed in this work used the data's of COVID-19 cases in India.FindingsThis study proposes a pediatric and geriatric people immunity network model for COVID- 19 patients. For the analysis part, the data's on COVID-19 cases in India was used. In this model, the authors have taken two sets of people (pediatric and geriatric), both are facing common symptoms such as fever, cough and myalgia. From the analysis, it was observed and also proved that the immunity level of patients decides the recovery rate of COVID-19 patients and the age of COVID-19 patients has no significant influence on the recovery rate of the patient.Originality/valueCOVID-19 has created a global health crisis that has had a deep impact on the way we perceive our world and our everyday lives. Not only the rate of contagion and patterns of transmission threatens our sense of agency, but the safety measures put in place to contain the spread of the virus also require social distancing. The novel model in this work focus on the Indian scenario and thereby may help Indian health organizations for future planning and organization. The factors model in this work such as age, immunity level, recovery rate can be used by machine leaning models for predicting other useful outcomes.

Social economic impact of COVID-19 outbreak in India

Purpose of this study: The situations of COVID-19 will certainly have an adverse effect over and above health care on factors of the internet of things (IoT) market. To overcome all the above issues, IoT devices and sensors can be used to track and monitor the movement of the people, so that necessary actions can be taken to prevent the spread of coronavirus disease (COVID-19). Mobile devices can be used for contact tracing of the affected person by analyzing the geomap of the travel history. This will prevent the spread and reset the economy to the normal condition. Design/methodology/approach: To respond to the global COVID-19 outbreak, the social-economic implications of COVID-19 on specific dimensions of the global economy are analyzed in this study. The situations of COVID-19 will certainly have an adverse effect over and above health care on factors of the IoT market. To overcome these issues IoT devices and sensors can be used to track and monitor the movement of the people so that necessary actions can be taken to prevent the spread of COVID-19. Mobile devices can be used for contact tracing of the affected person by analyzing the geomap of the travel history. This will prevent the spread and reset the economy to the normal condition. A few reviews, approaches, and guidelines are provided in this article along these lines. Moreover, insights about the effects of the pandemic on various sectors such as agriculture, medical industry, finance, information technology, manufacturing and many others are provided. These insights may support strategic decision making and policy framing activities for the top level management in private and government sectors. Findings: With insecurities of a new recession and economic crisis, key moments such as these call for strong and powerful governance in health, business, government, and large society. Instant support measures have to be initiated and adapted for those who can drop through the cracks. Mid- and long-term strategies are required to stabilize and motivate the economy during this recession. Originality/value: A comprehensive social-economic development strategy that consists of sector by sector schemes and infrastructure that supports business to ensure the success of those with reliable and sustainable business models is necessary. From the literature analysis and real world observations it is concluded that the IoT, sensors, wearable devices and computational technologies plays major role in preserving the economy of the country by preventing the spread of COVID-19.

IoT role in prevention of COVID-19 and health care workforces behavioural intention in India-an empirical examination

Purpose This paper aims to address the role of Internet of Things (IoT) in preventing COVID-19. The IoT devices can be used in various ways to track the patients and suspected person. Remote data collection can be done with the help of IoT and sensors. Later, the data can be analyzed with the help of data science engineers and researchers to predict and prevent the COVID-19. Design/methodology/approach IoT is a creative mean of amalgamating clinical gadgets and their applications to associate with the human services and data innovation frameworks. An investigation on the conceivable outcomes of defying progressive COVID-19 pandemic by implementing the IoT approach while offering treatment to all classes of patient without any partiality in poor and rich. The information sharing, report checking, patient tracking, data social affair, investigation, cleanliness clinical consideration and so forth are the different cloud-based administrations of IoT. It can totally change the working format of the medical services while rewarding the huge volume of patients with a predominant degree of care and more fulfilment, particularly during this pandemic of COVID-19 lockdown. Health workers can quickly focus on patient zero and identify everyone who has come into contact with the infected person and move these people to quarantine/isolation. As COVID-19 has emerged from the Wuhan province of China, IoT tools such as geographic information system could be used as an effective tool to curb the spread of pandemics by acting as an early warning system. Scanners at airports across the world could be used to monitor temperature and other symptoms. This paper addresses the role of IoT in preventing COVID-19. Findings In the period of continuous pandemic of COVID-19, IoT offers many propelled cloud-based administrations and offices to serve a greater number of patients effectively. The remote medicinal services framework provides a lot of significance in such a crucial time of lockdown. The powerful interconnected arrangement of gadgets, applications, Web, database and so on encourages the consumers to benefit the administrations in smart way. IoT additionally advances its administrations by building up the quality culture of perceptive medicinal services or portable centre. It is a "distinct advantage innovation," which may totally change the practices universally. Indeed, even its quality administrations in this extreme time make this methodology progressively productive and beneficial. IoT helps in observing and tracking more recognized people and patients in remote areas for their human service prerequisites. The customary medicinal services are probably going to observe a huge change in perspective sooner rather than later, as the computerized revolution would place cutting-edge innovation and its associated items in the possession of the patients and give both patients and doctors in remote areas better access to quality clinical services. Originality/value The contemporary exploration study focuses on the proposed IoT system for the treatment of patients in this progressing COVID-19. The working principle of IoT approach incorporates the mix of human services apparatuses, clinical treatment framework, Web organize, programming and administrations. IoT framework empowers the information assortment, report observing, understanding database, testing pictures and investigation and so forth. Data has been collected through online mode;in this study, the authors adopted empirical research design. Total 150 (118/150 = 78. 66% respondent response ratio) online questionnaires were sent in the Chennai city of Tamilnadu, India. The participated nature of work is clinical examination in critical care division.