ABSTRACT
The dreadful coronavirus has not only shattered the lives of millions of people, but it has also placed enormous strain on the whole healthcare system. In order to isolate positive cases and stop the disease from spreading, early detection of COVID-19 is crucial. Currently, a laboratory test (RT-PCR) on samples collected from the throat and nose is required for the official diagnosis of COVID-19. Specialized tools are needed for the RT-PCR test, which takes at least 24 hours to complete. It may often provide more false negative and false positive results than expected. Therefore, using X-ray and CT scan images of the individual's lung, COVID-19 screening can be used to support the conventional RTPCR methods for an accurate clinical diagnosis. The importance of chest imaging in the emergence of this lung illness has been recognized. Images from the computed tomography (CT) scan and chest X-ray (CXR) can be used to quickly and accurately diagnose COVID-19. However, CT scan pictures have their own drawbacks. In order to assess the effectiveness of chest imaging approaches and demonstrates that CXR as an input may compete with CT scan pictures in the diagnosis of COVID-19 infection using various CNN based models, this article thoroughly covers modern deep learning techniques (CNN). For CXR and CT scan pictures, we have evaluated with ResNet, MobileNet, VGG 16, and EfficientNet. Both chest X-ray (3604 Images) and CT scans (3227 images) from publicly accessible databases have been evaluated, and the experimental outcomes are also contrasted. © 2022 IEEE.
ABSTRACT
Background: Assessments of the blood donors’ knowledge, attitudes, practices, and perceptions of this infection are essential for controlling the spread of COVID-19. Aim and objectives: This study aimed to evaluate the KAP among blood donors towards COVID 19 pandemic and how to increase the number of blood donations during pandemic. Materials and Methods: This study was conducted among 630 blood donors at the Department of Transfusion Medicine, at a tertiary care center in North India. It was an observational study. Statistical analysis: The data were analyzed using Kruskal-Wallis and Mann-Whitney test. To correlate variables Chi-square test was used. Results: The knowledge score of demographic variables marital status, education & occupation showed a significant association, while its association with age, gender, and religion was insignificant. The entire demographic variables under study showed a significant association with Attitude questionnaire 1. According to univariate analysis, the variables Intercept, Unemployed and Physical Labour showed significant impact on knowledge level with the corresponding effect size 0.10 and 0.022. Conclusions: This study reveals that blood donors have good knowledge with positive attitudes and practices. By improving the knowledge with the help of health education platforms, the number of blood donations will also increase. © 2022, Indian Association of Preventive and Social Medicine. All rights reserved.
ABSTRACT
Distance learning is a learning system that does not take place in one room and there is no face-to-face interaction between the teacher and the learner. This study aims to determine the impact of implementing distance learning in Indonesia from a commognitive point of view. This research is a descriptive type of research with a total of 543 participants who come from high school students in Pasuruan district, Indonesia. Data collection using a questionnaire. After the questionnaire is collected, it is analyzed using the Miles and Huberman method through reduction, display data, and conclusion, then it will be studied based on the commognitive theory. The results show that based on commognitive studies, students are more likely to still need a visual mediator as a visible object to be used as a communication medium, its realization depends on the material context. Students need to communicate to ask questions related to material that has not been understood. So it can be said that visual mediator is important during distance learning.
ABSTRACT
The COVID-19 pandemic has caused a worldwide health crisis, laying stress on existing health-care systems and causing an unprecedented financial crisis. In this situation, provision of homogenized, evidence-based care by all levels of health-care providers, including those in a low-resource setting, is of paramount importance. As a specialized offshoot of Tele-medicine, Tele-intensive care unit (Tele-ICU) offers an innovative solution in the care of critically ill COVID-19 patients, by off-site clinicians, using audio, video, electronic, and tele-communication links to leverage technical, informational, and clinical resources. Tele-ICU also helps overcome the shortage of expertise like intensivists in these settings and helps to take the clinical expert to the patient bedside by remote monitoring and supervision. Telemedicine applications can be classified into four basic types, according to the mode of communication, timing of the information transmitted, the purpose of the consultation, and the interaction between the individuals involved-be it doctor-to patient/caregiver or doctor to doctor. The benefits and concerns of tele-medicine have been described in detail.