Rapid detection of COVID-19 from chest X-ray images using deep convolutional neural networks

The entire world is suffering from the corona pandemic (COVID-19) since December 2019. Deep convolutional neural networks (deep CNN) can be used to develop a rapid detection system of COVID-19. Among all the existing literature, ResNet50 is showing better performance, but with three main limitations, i.e.: 1) overfitting;2) computation cost;3) loss of feature information. To overcome these problems authors have proposed four different modifications on ResNet50, naming it as LightWeightResNet50. An image dataset containing chest X-ray images of coronavirus patients and normal persons is used for evaluation. Five-fold cross-validation is applied with transfer learning. Ten different performance measures (true positive, false negative, false positive, true negative, accuracy, recall, specificity, precision, F1-score and area under curve) are used for evaluation along with fold-wise performance measures comparison. The four proposed methods have an accuracy improvement of 4%, 13%, 14% and 7% respectively when compared with ResNet50.

Rapid detection of COVID-19 from chest X-ray images using deep convolutional neural networks

The entire world is suffering from the corona pandemic (COVID-19) since December 2019. Deep convolutional neural networks (deep CNN) can be used to develop a rapid detection system of COVID-19. Among all the existing literature, ResNet50 is showing better performance, but with three main limitations, i.e.: 1) overfitting;2) computation cost;3) loss of feature information. To overcome these problems authors have proposed four different modifications on ResNet50, naming it as LightWeightResNet50. An image dataset containing chest X-ray images of coronavirus patients and normal persons is used for evaluation. Five-fold cross-validation is applied with transfer learning. Ten different performance measures (true positive, false negative, false positive, true negative, accuracy, recall, specificity, precision, F1-score and area under curve) are used for evaluation along with fold-wise performance measures comparison. The four proposed methods have an accuracy improvement of 4%, 13%, 14% and 7% respectively when compared with ResNet50.

Assessment of Readmission Risk Factors after Index Hospital Discharge for Covid-19 Patients

INTRODUCTION: During the COVID-19 pandemic, the burden on the healthcare system makes it critical to examine readmission patterns. In this study, we evaluated the readmission rates and risk factors associated with COVID-19 from the large SCCM Discovery VIRUS: COVID-19 Registry. METHOD(S): This was a retrospective, cohort study including hospitalized adult patients from 181 hospitals in 24 countries within the VIRUS: COVID-19 Registry. Demographic, clinical, and outcome data were extracted and divided into two groups: Patients with readmission with COVID-19 in 30 days from discharge and those who were not. A univariate analysis is done using chi-square and t-test as appropriate. Multivariable logistic regression was used to measure risk factor associations with 30-day readmission. RESULT(S): Among 20,283 patients, 1,195 (5.9%) were readmitted within 30 days from discharge. The median (IQR) age of readmitted patients was 66 (55-78) years and 45.2% were female, 60.2% were white, and 78.9% non-Hispanic. Higher odds of readmission were observed in patients aged >60 vs 18-40 years (OR 2.76;95% CI, 2.23-3.41), moderate COVID-19 disease (WHO Ordinal scale 4-5) vs Severe COVID-19 (WHO Ordinal scale 6-9) (OR 1.23;95% CI, 1.10-1.39), no ICU admission at index hospitalization (OR 1.70;95% CI, 1.32-1.80), and Hospital length of stay <=14 vs >14 days (OR 1.53;95% CI, 1.32-1.80) vs those not readmitted (p= < 0.001). Comorbidities including coronary artery disease (OR 2.14;95% CI 1.84-2.48), hypertension (OR 1.58;95% CI 1.40-1.78), congestive Heart Failure (OR 2.54;95% CI 2.16-2.98), chronic pulmonary disease (OR 2.26;95% CI 1.94-2.63), diabetes (OR 1.32;95% CI 1.17-1.49) or chronic kidney disease (CKD) (OR 2.41;95% CI 1.2.09-2.78) were associated with higher odds of readmission. In multivariate logistic regression adjusted for age group, hospital length of stay <=14 days and, highest WHO COVID-19 ordinal scale and index ICU admission coronary artery disease, congestive heart failure, chronic pulmonary disease, chronic kidney disease, hospital length of stay <=14 days and age >60 years remained independent risk factors for readmission within 30 days. CONCLUSION(S): Among hospitalized patients with COVID-19, those readmitted had a higher burden of comorbidities compared to those non-readmitted.

A systematic review of randomized controlled trials on survival rate of atraumatic restorative treatment compared with conventional treatment on primary dentition.

Background: In this COVID era, it's critical to promote nonaerosol procedures. Atraumatic restorative treatment (ART) is one of them, and it's particularly effective in children for lowering anxiety, enhancing dental health, and giving restorative care. Aim: The aim of this study was to assess the survival rate of ART compared with conventional treatment procedures in primary dentition. Materials and Methods: The review was done in accordance with the Preferred Reporting Items for Systematic reviews and Meta-analysis statement and is been registered in PROSPERO (CRD42021213729). The studies included comprised clinical investigations with randomized controlled trials (RCTs) which compared the survival rate of ART and conventional restorative treatments using the same or different restorative materials to treat carious lesion. RCTs in which ART was compared with conventional treatment on patients in the age group of 6-10 years with minimum follow-up of 6 months. Studies available as open access and free full text in PubMed, DOAJ, and Google Scholar databases, and published in English Language only were included in the study. Cochrane's collaboration tool for RCTs was used for the assessment of risk of bias. Results: The survival rate of single surface and multiple surface in primary dentition treated according to the ART compared with conventional treatment was found to be similar. Conclusion: The ART approach is equally helpful in managing dental caries in children and this method may be considered a useful intervention in clinical practice to enhance the dental health of children.

A Deep Analysis of Higher Education Cognitive and Psychological Learning Impact During Covid 19 Pandemic

Current scenario around the globe we can find that physical or face to face learning got a very big full stop for a long period of time. Virtual learning took its place, somewhat leaving behind both its positive and negative impact on the education sector. E-learning is playing a chief part in maintaining the decorum of education sector. The research and surveys found that young learners got many benefits through this type of education but also it is undeniable that it has negative aspects too, which needs to be solved. Mainly private higher education suffered less as compared to institutions in rural areas. This research proposes how to bring out the quality of output through e-learning for all the learners equally. It has become a challenge for private and government institutions to make this smart or virtual learning as the best integral part of educational system. © 2021 The authors and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).