ABSTRACT
Battling the progressing Covid sickness 2019 (COVID-19) pandemic requests precise, quick, and point-of-care testing with quick outcomes to anticipate stages for isolation and therapy. The preliminary test to detect COVID-19 is a Swab test and also a Blood test, but these tests will take more than 2 days to receive the results and there is also a risk of transmission of the virus while collecting the samples. To predict the stages of COVID-19's effects on the human lungs accurately for further treatment for further diagnosis on a radiological image, medical experts need a high level of precision. We utilize image processing techniques and convolutional networks to analyze CT images of COVID-19 affected human lungs in this paper for the detection of pulmonary abnormalities in the early stage, Chest X-Ray is not exact. So, we are using Computed Tomography (CT) imaging especially for identifying the stages of lung anomalies. We present and discuss the scoring systems which cause the severity in lungs of COVID-19 patients every day. This will be accurate for predicting the stages of COVID-19 for early treatment and also to protect the uninfected population. © 2022 IEEE.
ABSTRACT
The use of health apps on mobile devices by healthcare providers and receivers (patients) is proliferating. This has elevated cybersecurity concerns owing to the transmittal of personal health information through the apps. Research literature has mostly focused on the technology aspects of cybersecurity in mobile healthcare. It is equally important to focus on the ethical and regulatory perspectives. This article discusses cybersecurity concerns in mobile healthcare from the ethical perspective, the regulatory/compliance perspective, and the technology perspective. The authors present a comprehensive framework (DeTER) that integrates all three perspectives through which cybersecurity concerns in mobile healthcare could be viewed, understood, and acted upon. Guidance is provided with respect to leveraging the framework in the decision-making process that occurs during the system development life cycle (SDLC). Finally, the authors discuss a case applying the framework to a situation involving the development of a contact tracing mobile health app for pandemics such as COVID-19. © 2021 IGI Global. All rights reserved.
ABSTRACT
Background: In India, 8.27 million documented cases of COVID 19 and a total of 123K deaths have been reported till October 2020. We were able to estimate the clinical consequences of SARS CoV 2 in 16 patients over a period of 5 months. The disease prevalence and mortality rate observed in transplant recipients were found to be higher than in the general population. Aims and Objectives: A retrospective analysis of COVID 19 infections in kidney transplant recipients and the outcome. Materials and Methods: A single centre observational study of all patients who have undergone kidney transplant between March 2001 and December 2019 and documented evidence of SARS CoV 2 infection between March 2020 and October 2020. From a large cohort of 720 kidney transplant recipients, 16 recipients who developed COVID 19 infection were studied. They were all on maintenance immunosuppression in varying doses. None of the patients in this cohort had any recent episodes of cellular rejection requiring heightened immunosuppression. The vintage of the transplant varied from 9 to 192 months. Results: Acute kidney injury was identified in two patients. Eight patients were home quarantined and eight patients were hospitalized. All patients had a reduction in immunosuppression during the covid 19 infection dosage based on the severity of the disease. Out of the hospitalized patients, three died, two of whom had stable functioning grafts and the cause of death was identified as acute lung injury 1 patient had post covid ACR which was treated with Injection. Methyl Prednisolone. Conclusions: In our study, 2.22% developed COVID-19 disease and the mortality rate was 18.75% among those who developed COVID-19. The disease prevalence and mortality rate observed in transplant recipients were found to be higher than in the general population. Obesity, diabetes mellitus, and systemic hypertension were identified as independent risk factors.