ABSTRACT
COVID-19 is a transferable disease inherited from the SARS-CoV-2 virus. A total of 594 million people have been infected, and 6.4 million human beings have died due to COVID-19. The fastest way to diagnose the disease is by radiography. Deep learning has been the most popular technique for image classification during the last decade. This paper aims to examine the contributions of machine learning for the detection of COVID-19 using Deep Learning and explores the overall application of convolutional neural networks of some famous state-of-the-art deep learning pre-trained models. In this research, our objective is to explore the various image classification strategies for CXIs and the application of deep learning models for optimization and feature selection. The study presented in this article shows that the accuracy of deep learning models when detecting COVID-19 on the basis of chest X-ray images ranges from 93 percent to above 99 percent.
ABSTRACT
In this trying time for the world battling different variants of the COVID'19 pandemic, different intervention strategies are being taken by government, to limit the spread of infection. Closing educational institutes, stay at home orders, campaigns for emphasis on vaccination, usage of medical mask and frequently sanitizing hands, etc. are the endeavors made by the authorities to decrease the number of cases in the country. In this regard, the contribution aims to help the decision-makers to identify a potential prevention strategy, based on public acceptance and intervention effectiveness. To achieve this objective, feasible judgments of professionals from three different sectors are brought together through meetings. Opinions, based on ten criteria, are recorded in linguistic form for prioritizing six alternatives. The linguistic terms are then evaluated and manipulated by entailing triangular fuzzy numbers and a group multi-criteria decision making (GMCDM) approach. After using the fuzzy analytical hierarchy process (F-AHP) for the complex decisions, the fuzzy VIsekriterijumsko KOmpromisno Rangiranje method (F-VIKOR) is utilized to attain the closest ideal stratagem. Consequently, through the ranking orders of defuzzified scores, intuitive preference of compromise solutions is suggested. The tactic gaining more priority with respect to the group utility to the majority and F-VIKOR index is complete lockdown for the short term. Furthermore, a comparison analysis is also added in the discussion to verify the attained prioritized outcomes. This comparative study is carried out through the technique for order of preference by similarity to ideal solution (TOPSIS), which evidently produces the same preference of alternatives. In addition, this strategy can be apparently discovered to be an effective strategy adopted by different countries in successfully decreasing the number of cases.
ABSTRACT
Abstract: Information seeking through the media(mainstream and social media) plays a pivotal role in affecting health behavior of a population at risk during a health crisis. Health Belief Model(HBM) has been widely used to understand and analyze health behavior through its variables including(perceived) knowledge, susceptibility, severity, motivation, self-efficacy, benefits, barriers and cues to action. This study investigates the relationship of information seeking through TV and Facebook with various HBM variables on population of province of Punjab(Pakistan) during Covid-19 pandemic 2019-20. Data were collected through modified Champion Scale(Champion, 1993) from a sample of one thousand respondents selected through simple random sampling technique via online google forms. It is found that for both TV and Facebook correlation coefficient is significant between information seeking and all HBM variables except Facebook with perceived knowledge and benefits. The values of coefficient indicate overall weak correlations however TV has more powerful correlation than Facebook. For HBM variables, respondents do not perceive covid-19 as a severe threat. Moreover, it is found that citizens give preference to get information from international sources as compared to governments(federal and provincial) and reporters and anchors that stand last for seeking information to modify health behavior for covid-19 pandemic in Punjab, Pakistan.