Pre-text Representation Transfer for Deep Learning with Limited and Imbalanced Data: Application to CT-Based COVID-19 Detection

Annotating medical images for disease detection is often tedious and expensive. Moreover, the available training samples for a given task are generally scarce and imbalanced. These conditions are not conducive for learning effective deep neural models. Hence, it is common to ‘transfer' neural networks trained on natural images to the medical image domain. However, this paradigm lacks in performance due to the large domain gap between the natural and medical image data. To address that, we propose a novel concept of Pre-text Representation Transfer (PRT). In contrast to the conventional transfer learning, which fine-tunes a source model after replacing its classification layers, PRT retains the original classification layers and updates the representation layers through an unsupervised pre-text task. The task is performed with (original, not synthetic) medical images, without utilizing any annotations. This enables representation transfer with a large amount of training data. This high-fidelity representation transfer allows us to use the resulting model as a more effective feature extractor. Moreover, we can also subsequently perform the traditional transfer learning with this model. We devise a collaborative representation based classification layer for the case when we leverage the model as a feature extractor. We fuse the output of this layer with the predictions of a model induced with the traditional transfer learning performed over our pre-text transferred model. The utility of our technique for limited and imbalanced data classification problem is demonstrated with an extensive five-fold evaluation for three large-scale models, tested for five different class-imbalance ratios for CT based COVID-19 detection. Our results show a consistent gain over the conventional transfer learning with the proposed method. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Covid-19 Pandemic: Global Scenario, Socialdeterminants and Its Socio-Economic Impact

Background: The COVID-19 pandemic has resulted in about 75.2M cases and 1.67M deaths worldwide, as on 18th December 2020 data live updates of World Health Organizations. In response to this pandemic, this study analyzes the global issue of rising and falling of COVID-19 cases and changing scenario of economies. Method(s): The data has been extracted from January 2020 to December 2020 from some of the reliable sources of the World like WHO Coronavirus disease (COVID-19) dashboard, Worldometer, and Centers for Disease Control and Prevention (CDC). It also represents the global scenario of the COVID-19 pandemic and its social determinants around the world. Result(s): There has been spatial heterogeneity in the number of cases and the number of deaths among regions worldwide. There is a great impact on the countries economy, both on the supply and demand side. It shows that several factors affect the determinants of health at various levels like income, healthcaresystem, education, etc also play a major role in it. Conclusion(s): The increasing cases worldwide have adversely affected the economy and have led to a scarcity of resources which further caused the collapse of the economy and trade.Copyright © 2020 Ubiquity Press. All rights reserved.

Impact of climatic factors on viability of SARS-CoV-2 and transmission prospective of COVID-19: An overview

The emergence of the new coronavirus disease-19 (Covid-19) from exotic wild animal market in Hubei, China during the late December 2019 has spread in 250 countries and territories posing menace to health of people around the globe. Coronavirus disease-19 has a great impact on public health, mortality and economy. The causing agent of Covid-19 is severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Due to unavailability of the potential drug or treatment for Covid-19, multi factorial research is conducted to reduce its transmission. Climatic factors play a key role in regulating the transmission of the infectious diseases like Severe Acute Respiratory Syndrome (SARS), Middle East Respiratory syndrome, and influenza. So, the rate of prevalence of the infectious disease is likely to be inclined by the variation in climatic indicators. We conclude from the past and present experiences that coronavirus transmission is elevated under low temperature and high humidity and vice versa. It further infers that after three hours of incubation of SARS-CoV-2, no infectious virus could be recovered from tissue paper and printing. Smooth surfaces are found to be more favorable for SARS-CoV-2. We may infer that climatic variations greatly affects infectious disease transmission pattern. We need more to study about under laying multifaceted casual affiliation between climate and communicable diseases and employ this information to the forecast of their upcoming impact. © 2020 The author (s).

Global retailers' CSR initiatives during COVID-19 crisis: a cross-cultural examination

Purpose: This study develops a conceptual framework to examine (1) whether global retailers' CSR actions in the form of in-kind charitable contribution affect consumers' attribution of CSR to intrinsic motives, (2) whether consumers' attribution of CSR to intrinsic motives affects brand-self connection and (3) whether the cultural factors of self-transcendence and conservation moderate the relationship between consumers' attribution of CSR to intrinsic motives and brand-self connection. Design/methodology/approach: Data are collected from two culturally diverse countries, the US and China, each of which managed the pandemic in different ways. Before hypothesis testing, the invariance of measures is established. To measure differences between the groups, a multi-group analysis is conducted. Findings: Global retailers' in-kind charitable contribution is a significant drivers of consumers' attribution of CSR to intrinsic motives, and attribution of CSR to intrinsic motives has a positive effect on consumer brand-self connection. Both of the cultural values, self-transcendence and conservation, moderate the relationship between attribution of CSR to intrinsic motives and brand-self connection. Self-transcendence is a strong moderator in China, whereas conservation moderates strongly in the US. All of the relationships differ significantly between the groups (US versus China). Originality/value: To the best of our knowledge, this is the first study to investigate empirically the role of in-kind charitable contribution in creating an attribution of CSR to intrinsic motives that eventually leads to strong brand-self connection in the COVID-19 context. The study provides novel insights into how consumer behavior differs across two significantly different cultures with regard to COVID-19-related CSR. The findings help international marketers manage uncertainties and crisis and to design their CSR-based marketing programs and develop positioning strategies across cultures. © 2023, Emerald Publishing Limited.

Bioinspired NC Coated BM-ZIF for Electrochemical Monitoring of Adrenaline from Blood and Pharmaceutical Samples

Herein, we have developed highly sensitive and selective non-enzymatic bioinspired polydopamine derived nitrogen rich carbon (NC) coated bimetallic zeolitic imidazolate framework (BM-ZIF) electrochemical sensor via simple hydrothermal approach for monitoring adrenaline (AD) from COVID-19 quarantined person blood and pharmaceutical sample. The designed NC-BM-ZIF electrode shows excellent sensitive and selective performance towards AD monitoring with detection limit (LOD) of 0.01 nM and 0.1931 μA/nM/cm2 sensitivity over a wide linear range of 50–1625 nM. To the best of our knowledge, this is the first study of using of NC-BM-ZIF electrode for the electrochemical sensing of AD from quarantined person blood and pharmaceutical sample. © 2022 Wiley-VCH GmbH.

Evaluation of safety and efficacy of Unani Add-on regimen in preventing the progression of severity of the disease in hospitalized SARS-CoV2 tested positive asymptomatic /mild to moderate symptomatic COVID-19 cases-A Randomised Controlled Clinical Trial

Objectives: The study aimed to establish the effectiveness of Unani add-on regimen by comparing theduration required for change in disease status from COVID-19 positive asymptomatic / mildto moderate symptomatic patients to asymptomatic negative. Methods: This single-centric, randomized, twin arm, controlled, clinical trial was carried out on a totalnumber of 62 RT-PCR confirmed COVID-19 patients. The Intervention group (IG) receivedUnani Regimen (Khameera Marwareed and Unani Joshanda) in addition to the conventional management, while the Control group (CG) received only conventional management. Results: It was observed that 16 (51.6%) patients in Intervention Group and 3 (9.4%) patients incontrol group became negative for COVID-19 at day 7 and remaining 13 out of 15 (93.5%) patients in Intervention Group and 20 out of 28 (74.1%) patients in control group becamenegative for COVID-19 at day 14.This effect of the Unani Regimen in comparison to thecontrol group was statistically significant (p =0.003). Conclusions: It can be concluded that the change of COVID-19 positive asymptomatic / mild to moderate symptomatic patients to RT-PCR negative was much earlier in the add-on Unani regimen group as compared to control group.

A Novel Algorithm to Secure Data in New Generation Health Care System from Cyber Attacks Using IoT

The rise of digital technology has essentially enhanced the overall communication and data management system, facilitating essential medical care services. Considering this aspect, the healthcare system successfully managed patient requirements through online services and facilitated patient experience. However, the lack of adequate data security and increased digital activities during Covid-19 made the healthcare system a soft target for hackers to gain unauthorized access and steal crucial and sensitive information. Countries such as the UK and the US recently received such challenges, highlighting the need for effective data maintenance. IoT emerged as one of the critical solutions for data management systems in terms of addressing data security which certainly can enhance overall data collection, storage, maintenance, prediction of potential data security breaches and taking appropriate measurements. The concerned research considers a secondary data collection process where necessary data is collected from original scholarly articles, books and journals. Apart from that, a positivism research philosophy, a deductive research approach and a descriptive research design have been considered for this study. Qualitative data analysis techniques have also been incorporated into this research. Upon viewing the pros and cons of IoT algorithms, DES, AES, triple data encryption standards, and RSA encryption can be used in the healthcare system to facilitate data protection. © 2022 by Addanki Kavitha, B Srinivasa Rao, Dr Nikhat Akhtar, Dr Shaik Mohammad Rafi, Prabhdeep Singh, Dr Sunanda Das and Dr G Manikandan.

Resetting the baseline: CT-based COVID-19 diagnosis with Deep Transfer Learning is not as accurate as widely thought

Deep learning is gaining instant popularity in computer aided diagnosis of COVID-19. Due to the high sensitivity of Computed Tomography (CT) to this disease, CT-based COVID-19 detection with visual models is currently at the forefront of medical imaging research. Outcomes published in this direction are frequently claiming highly accurate detection under deep transfer learning. This is leading medical technologists to believe that deep transfer learning is the mainstream solution for the problem. However, our critical analysis of the literature reveals an alarming performance disparity between different published results. Hence, we conduct a systematic thorough investigation to analyze the effectiveness of deep transfer learning for COVID-19 detection with CT images. Exploring 14 state-of-the-art visual models with over 200 model training sessions, we conclusively establish that the published literature is frequently overestimating transfer learning performance for the problem, even in the prestigious scientific sources. The roots of overestimation trace back to inappropriate data curation. We also provide case studies that consider more realistic scenarios, and establish transparent baselines for the problem. We hope that our reproducible investigation will help in curbing hype-driven claims for the critical problem of COVID-19 diagnosis, and pave the way for a more transparent performance evaluation of techniques for CT-based COVID-19 detection.

BOOSTING DEEP TRANSFER LEARNING FOR COVID-19 CLASSIFICATION

COVID-19 classification using chest Computed Tomography (CT) has been found pragmatically useful by several studies. Due to the lack of annotated samples, these studies recommend transfer learning and explore the choices of pre-trained models and data augmentation. However, it is still unknown if there are better strategies than vanilla transfer learning for more accurate COVID-19 classification with limited CT data. This paper provides an affirmative answer, devising a novel ‘model’ augmentation technique that allows a considerable performance boost to transfer learning for the task. Our method systematically reduces the distributional shift between the source and target domains and considers augmenting deep learning with complementary representation learning techniques. We establish the efficacy of our method with publicly available datasets and models, along with identifying contrasting observations in the previous studies. © 2021 IEEE

Does social media usage boost career prospects of women: an exploratory study in the academia

Purpose This paper draws on the affordance perspective, to explore the social media (SM) usage experiences that might render valuable for academic women professionals, for knowledge exchange, networking and success. Owing to the increased SM usage during COVID-19 pandemic, this paper tries to find out that in what ways do SM affordances facilitate the underprivileged group of women professionals to grow in their careers in a masculine, conservative society through knowledge exchange. Design/methodology/approach By utilizing qualitative study design, the authors collected data from 31 women employed in Pakistani universities, through unstructured questionnaires. The responses were analyzed through Nvivo. Findings The generated themes suggested that women in Pakistan are aware of SM's potential for knowledge exchange among fellow professionals. They use it to aid them in communication, collaboration and networking. Additionally, they utilize it to share knowledge and build networks that are vital for career progression and success. Research limitations/implications The paper concludes with the implications for practitioners that would aid them in boosting career prospects for women academicians through SM usage in a developing country Pakistan;where women's career outlooks are not as promising as for men;or as bright as for women working in the developed economies. Originality/value This a unique attempt to explore knowledge exchange dimensions with the help of SM in the context of working women by the deploying the phenomenological approach.

How does psychosocial safety climate affect burnout among malaysian educators during the covid-19 pandemic?

Nowadays, the COVID-19 pandemic has led Malaysian educators to experience more significant burnout due to job demands. This paper is an effort to examine the reasons that caused burnout among Malaysian educators. A total of 413 Malaysian educators participated in the study. This study’s findings revealed that PSC has a significant negative relationship with hindrance demands and burnout, whereas both challenge and hindrance demands have insignificant positive relationships with burnout. Furthermore, the study showed that two variables—challenge demands and hindrance demands—played significant mediators in the relationship between PSC and burnout. As a result, it is concluded that PSC can reduce the unfavorable characteristics of hindrance demands and burnout among Malaysian educators. This paper’s findings are valuable to academics and experts who wish to minimize the burnout pervasiveness among Malaysian educators. © 2021 by De La Salle University.

Changes in neuro-endovascular procedural volume during the Covid-19 Pandemic: An international multicenter study

Objective: The effect of Coronavirus disease 2019 (COVID-19) pandemic on performance of neuro-endovascular procedures has not been quantified. Background: The effect of Coronavirus disease 2019 (COVID-19) pandemic on performance of neuro-endovascular procedures has not been quantified. Design/Methods: We performed an audit of performance of neuro-endovascular procedures at 18 institutions (7 countries) for two periods;January to April 2019 and 2020, to identify changes in various core procedures. We divided the region where the hospital was located based on the median value of total number of COVID-19 cases per 100,00 population-into high and low prevalent regions Results: Between 2019 and 2020, there was a reduction in number of cerebral angiograms (30.9% reduction), mechanical thrombectomy (8% reduction), carotid artery stent placement for symptomatic (22.7% reduction) and asymptomatic (43.4% reduction) stenoses, intracranial angioplasty and/or stent placement (45% reduction), and endovascular treatment of unruptured intracranial aneurysms (44.6% reduction) and ruptured (22.9% reduction) and unruptured brain arteriovenous malformations (66.4% reduction). There was an increase in treatment of ruptured intracranial aneurysms (10% increase) and other neuro-endovascular procedures (34.9% increase). There was no relationship between procedural volume change and intuitional location in high or low COVID-19 prevalent regions. The procedural volume reduction was mainly observed in March-April 2020. Conclusions: We provided an international multicenter view of changes in neuro-endovascular practices to better understand the gaps in provision of care and identify individual procedures which are susceptible to change.

Global impact of the COVID-19 pandemic on stroke care and intravenous thrombolysis

Objective: The objectives of this study were to measure the global impact of the pandemic on the volumes for intravenous thrombolysis (IVT), IVT transfers, and stroke hospitalizations over 4 months at the height of the pandemic (March 1 to June 30, 2020) compared with two control 4-month periods. Background: The COVID-19 pandemic led to widespread repercussions on the delivery of health care worldwide. Design/Methods: We conducted a cross-sectional, observational, retrospective study across 6 continents, 70 countries, and 457 stroke centers. Diagnoses were identified by ICD-10 codes and/or classifications in stroke center databases. Results: There were 91,373 stroke admissions in the 4 months immediately before compared to 80,894 admissions during the pandemic months, representing an 11.5% (95%CI,-11.7 to-11.3, p<0.0001) decline. There were 13,334 IVT therapies in the 4 months preceding compared to 11,570 procedures during the pandemic, representing a 13.2% (95%CI,-13.8 to-12.7, p<0.0001) drop. Interfacility IVT transfers decreased from 1,337 to 1,178, or an 11.9% decrease (95%CI,-13.7 to-10.3, p=0.001). There were greater declines in primary compared to comprehensive stroke centers (CSC) for stroke hospitalizations (-17.3% vs-10.3%, p<0.0001) and IVT (-15.5% vs-12.6%, p=0.0001). Recovery of stroke hospitalization volume (9.5%, 95%CI 9.2-9.8, p<0.0001) was noted over the two later (May, June) versus the two earlier (March, April) months of the pandemic, with greater recovery in hospitals with lower COVID-19 hospitalization volume, high volume stroke center, and CSC. There was a 1.48% stroke rate across 119,967 COVID-19 hospitalizations. SARS-CoV-2 infection was noted in 3.3% (1,722/52,026) of all stroke admissions. Conclusions: The COVID-19 pandemic was associated with a global decline in the volume of stroke hospitalizations, IVT, and interfacility IVT transfers. Primary stroke centers and centers with higher COVID19 inpatient volumes experienced steeper declines. Recovery of stroke hospitalization was noted in the later pandemic months, with greater recovery in hospitals with lower COVID-19 hospitalizations, high volume stroke centers, and CSCs.

COVID-19: A Burden on the Indian Healthcare System

The COVID-19 cases and the death toll are increasing in India with time so is the demand for an improved healthcare system. This critical situation demands a huge medical infrastructure with sufficient medical personnel. This pandemic has also led to an increase in demand for medical equipment in different parts of India, which is causing clinical consternations during treatment procedures. This paper confers the current situation being faced by the healthcare system in India and provide a descriptive analysis of the current situation, which would act as a situational guide for the policymakers. This paper has also reviewed recent literature on the current healthcare crises including the occurrence of mucormycosis in India and even highlights the shortcomings of the vaccination policy in the country. © 2021 New Zealand Mathematical Society and Department of Mathematics, University of Auckland.

Pregnancy Outcome in COVID-19 Suspected and COVID-19 Confirmed Women: A Comparative Analysis

Objective: To determine pregnancy outcome in COVID-19 suspected and confirmed women presenting to a tertiary care hospital. Methods: An analytical study comparing clinical outcome of confirmed COVID-19 with suspected COVID-19 pregnant women was carried out during three-month period from 1st July to 30th September 2020 at COVID-19 ward on pregnant women of Sir Ganga Ram Hospital Lahore. Information including clinical features, obstetrical outcome, ventilatory support and mortality was collected on a predesigned Proforma. The data were analyzed by using SPSS version 24. Qualitative data were expressed as frequency, percentages and chi-square, While quantitative variables as mean +/- SD. Results: Eighty-three patients were enrolled, including 41 confirmed and 42 suspected COVID-19 cases. The mean age was 28.59 years +/- 4.9. The mean gestational age on admission was 31.98 weeks. Obstetrical complications included miscarriage in 5 (11.6%) cases, preterm labor in 5 (11.6%), PPROM in 1 (2.3%) and IUD in 2 (4.7%) in COVID-19 suspect group. A total of 17/41 confirmed and 19/42 suspected COVID-19 were delivered during the study mostly through caesarean section. Supplemental oxygen, ICU admission, and invasive mechanical ventilation were more common in COVID-19 suspect group compared to confirmed COVID-19 group. There were 12(28.5%) mortalities in COVID-19 suspect group as compared to 2/41 (4.8%) in confirmed COVID-19 group. Conclusion: In patients having epidemiological exposure, clinical features of COVID and suggestive chest X-ray/CT chest findings even with negative COVID-19 PCR, high index of suspicion of COVID-19 must be mainstay to prevent delayed management and disease spread till the availability of more sensitive test.

Service Innovation Readiness of Health Institutions during COVID-19: A Perspective from the Kingdom of Saudi Arabia

The purpose of the research was to explore the factors which affect service innovation in organizations and how the utilization of resources can improve organizational performance, and gain a competitive advantage by adopting numerous innovative practices. This study hypothesizes Service Innovation Readiness (SIR) to consist of Strategic Alignment favoring Service Innovation (SASI) and Empowering Structure for Service Innovation (ESSI), which regulate the organization's preparedness to adopt service innovation changes. Six dimensions were identified and analyzed to understand their effects on SASI and ESSI. A structured questionnaire on a 5-point Likert scale was used to collect data from the selected hospitals of Saudi Arabia. The research results contribute considerably to the subject matter by theorizing SIR and the complex variable settings essential for embracing SI. This research also provides some understanding of the service innovation management dimension through a complete assessment that measures the organization's readiness and attempts to direct organizations' efforts to achieve and sustain competitive advantage. The study conducted is unique in the current geographic limits and has explored numerous SI areas of an organization's readiness to adopt service innovation.

P-Tracer: Proximity Detection for Contact Tracing

COVID-19 pandemic has impacted millions of people worldwide. To tackle the spread of disease, governments all over the world had to impose sudden lockdowns with strict restrictions and has resulted in stressing most of the enterprises on the financial fronts. As the governments all over the world are now relaxing the restrictions, businesses are re-opening gradually and employees are returning back to work. There is huge responsibility on the enterprises to stay vigilant when an employee tests positive for COVID-19. To target the issue, we have come up with a contact tracing solution, P-Tracer application which uses users wifi association data from Arista Networks' Cloud-Vision Wifi. This paper shortly presents the P-Tracer application working principle. We claim that the application will be useful in tracing the users association journey and detection of new hot zones and possible new cases. © 2021 IEEE.