ABSTRACT
Novel coronavirus disease 2019 (COVID-19) has become a public health concern with over 6.5 million cases and 390,000 deaths around the world. This research aimed to find an association between computed tomography (CT) scores and clinical and laboratory findings to estimate the extent of lung infection in patients with COVID-19. The study sample enrolled 129 patients diagnosed with COVID-19 from January to February 2020. The chest CT images and clinical data were reviewed, images were segmented and scored by the degree of involvement from 0 to 4, and the relationship between them and clinical and laboratory findings were analyzed statistically. This study included 74 men and 59 women with a mean age of 55.08 years. Different abnormalities were observed;the mean CT score was 8.52 (7.83 to 9.21) and the most frequent lesions were GGO and consolidation. Our results revealed significant differences between groups categorized by dyspnea, sore throat, and low oxygen saturation concerning CT scores. There was also a significant correlation between CT scores and WBC counts and CRP levels (P<0.05). The evidence from this study implies that clinical and laboratory data, such as CRP, dyspnea, lymphopenia, and symptom onset closely correspond to chest CT scores and may be employed as initial tools to estimate the extent of lung involvement in COVID-19 patients.Copyright © 2023 Tehran University of Medical Sciences.
ABSTRACT
Data Visualization plays an important role for patterns and trends analysis in trillion of data rows Big Data analysis, where the data can be represented in some graphical forms. Hence, the data could be more comprehensible in its visual summary in dashboards and storyboards. This study aims to discuss some issues and challenges in visualizing COVID-19 vaccination datasets. There are some possible issues in data visualization, as it is not easy and may be challenging to produce a good dashboard that are interesting and easy for viewers to understand. Therefore, this study focuses on some issues that may arise during performing a data visualization on the COVID-19 dataset. In this study, there are three dashboards have been studied, which are the COVID-19 tracker, its effectiveness, and its acceptance. The first two dataset are derived from Ministry of Health Malaysia bank data, whereas the third dataset is from a survey to support this analysis. The selected attributes are states, the number of people who have received the vaccine as adults, children, and teenagers, and the number of people who already received boosters, and reasons to not get a booster. The visualization issues found within the dashboard are mis-choice of colors, mis-choice of visual object type, lack of interactivity, and plotting too much data. As a result, this proposed alternative solutions for those issues such as color deliberately, pick a suitable visual object, create an interactive dashboard, and reduce the information overload in visualizing the data. © 2022 IEEE.
ABSTRACT
The rapid diffusion of social media applications is ushering in new possibilities for non-profit organisations to communicate with and engage the public. Social media can be a means of participation and engagement. In particular, it involves the delivery of information through social media that is directed to encourage public participation and engagement by providing comments, responses, and input to government agencies. Instagram, a mobile photo (and video) capturing and sharing service, has quickly emerged as a new medium in the spotlight in recent years. In this study, the researchers analysed the level of citizen engagement with Malaysia government ministries practices and calculated the engagement rate of each ministry on Instagram. This research was conducted for a period of one year which is from 1st January until 31st December 2020 through the formula of the Engagement Rate measurement. The data showed 21 accounts from 27 ministry Instagram accounts received a low Engagement Rate quality, which means 77.78% of ministry Instagram accounts had not been able to optimise their Instagram accounts to get engagement from their followers. Moreover, Engagement Rate is a very important measure for knowing Instagram optimisation. By knowing the Engagement Rate, we will find out how much influence the account has on followers. © 2022, Penerbit Universiti Kebangsaan Malaysia. All rights reserved.
ABSTRACT
Introduction: COVID-19 pneumonia is one of the critical health system challenges in the world. This study aimed to compare the imaging and staging findings of the COVID-19 pneumonia CT scan in patients with and without cancer. Methods: In this case-control study, 109 cancer patients as the case group and 214 non-cancer patients as the control group were included. Covid-19 patients with and without cancer referred to Amir Al-Momenin, and Khansari Hospital in Arak city from June 2020 to July 2021 were included. The data were organized into demographics, underlying medical conditions, ICU admission, and imaging findings. Results: Overall, 323 Covid-19 patients were included in the analysis, and 109 cases of them were cancer patients. The mean age was 63.12±15.38 years, and 53.87% were female. Intensive Care Unit (ICU) admission rate (41.28% vs 41.28%12.62%) was significantly higher in the cancer group than in the control group (P<0.001). The involvement of lung lobes in the cancer group was higher than in the control group (P=0.011) (70.56% in the left lung and 71.1% in the right lung of cancer patients than 77.40% in the left lung and 83.10% in the right lung). The presence of Ground Glass Opacities (GGO) was higher in CT images of the cancer group in all lobs. This difference in the right upper lobe (RUL) lob was significant (P=0.011) and consolidation (CON) was higher in CT images of the control group, but the differences were not significant (P>0.05). The mean total score in the cancer group was 6.23±2.76 and in the control group was 5.87±2.23 (P=0.202). The mean score in the cancer group of left lower lobe (LLL) lung lobes was 1.46±0.94 and in the control group was 1.21±0.76 (P=0.010) (Table 2). Conclusion: The results showed that GGO and consolidation were common findings in CT images. GGO was higher in cancer patients. The involvement of lung lobes in the cancer group was higher than in the control group. ICU admission rate was significantly higher in cancer patients.