ABSTRACT
The COVID-19 pandemic still affects most parts of the world today. Despite a lot of research on diagnosis, prognosis, and treatment, a big challenge today is the limited number of expert radiologists who provide diagnosis and prognosis on X-Ray images. Thus, to make the diagnosis of COVID-19 accessible and quicker, several researchers have proposed deep-learning-based Artificial Intelligence (AI) models. While most of these proposed machine and deep learning models work in theory, they may not find acceptance among the medical community for clinical use due to weak statistical validation. For this article, radiologists' views were considered to understand the correlation between the theoretical findings and real-life observations. The article explores Convolutional Neural Network (CNN) classification models to build a four-class viz. "COVID-19", "Lung Opacity", "Pneumonia", and "Normal"classifiers, which also provide the uncertainty measure associated with each class. The authors also employ various pre-processing techniques to enhance the X-Ray images for specific features. To address the issues of over-fitting while training, as well as to address the class imbalance problem in our dataset, we use Monte Carlo dropout and Focal Loss respectively. Finally, we provide a comparative analysis of the following classification models - ResNet-18, VGG-19, ResNet-152, MobileNet-V2, Inception-V3, and EfficientNet-V2, where we match the state-of-the-art results on the Open Benchmark Chest X-ray datasets, with a sensitivity of 0.9954, specificity of 0.9886, the precision of 0.9880, F1-score of 0.9851, accuracy of 0.9816, and receiver operating characteristic (ROC) of the area under the curve (AUC) of 0.9781 (ROC-AUC score). © 2022 ACM.
ABSTRACT
Today, it is impossible for a being to fathom living without a vehicle for transportation of any kind. All governments have put into place numerous regulations on the use of well-maintained vehicles to stop this, but there are always exceptions. The world is transitioning to an automated system that requires little human interaction as a result of the COVID-19 pandemic. This intelligent system involves identifying the predicting trends in the market analysis based on the expenses and revenues patterns of a particular group of people in a city or location. This the system needs to offer the insight into the direction for decision making of the market on demand of vehicle as per the supply with respect to the type of roads, season, and gender and age group patterns. Apartfrom this, the tax rules make a huge difference in this context. In some zones, many governments encourage by giving lots of subsidies or give tax relaxations to certain cc vehicles. In the future, based on the distance travelled, the system can impose tax fair or toll plaza fee. © 2023, IGI Global. All rights reserved.
ABSTRACT
Recent years have witnessed increased pressure across the global healthcare system during the COVID-19 pandemic. The COVID-19 pandemic shattered existing healthcare operations and taught us the importance of a resilient and sustainable healthcare system. Digitisation, specifically adoption of Artificial Intelligence (AI) has positively contributed to developing a resilient healthcare system in recent past. To understand how AI contributes to building a resilient and sustainable healthcare system, this study based on systematic literature review of 89 articles extracted from Scopus and Web of Science databases is conducted. The study is organised around several key themes such as applications, benefits, and challenges of using AI technology in healthcare sector. It is observed that AI has wide applications in radiology, surgery, medical, research, and development of healthcare sector. Based on the analysis, a research framework is proposed using an extended Antecedents, Practices, and Outcomes (APO) framework. This framework comprises AI applications' antecedents, practices, and outcomes for building a resilient and sustainable healthcare system. Consequently, three propositions are drawn in this study. Furthermore, our study has adopted the theory, context and methodology (TCM) framework to provide future research directions, which can be used as a reference point for future studies. © 2023 Informa UK Limited, trading as Taylor & Francis Group.
ABSTRACT
BACKGROUND: Rhino-orbital-cerebral mucor mycosis (ROCM) is a relatively rare opportunistic infection caused by the Mucorales species. While ROCM suggests involvement of the paranasal sinuses, orbit and brain ROM (rhino-orbital-Mucormycosis) stands for the fungal invasion in sinuses and orbit sans cerebral involvement. In India with the outbreak of the second COVID wave and the delta variant of the virus, there has been a steep increase in this opportunistic fulminant fungal infection, named COVID-associated Mucor mycosis (CAM). The most critical question in orbital management is when to go ahead with an exenteration. Our study aims to design a pertinent minimal invasive surgical protocol for surgeons to manage such cases based on our surgical experience and mitigate the need for exenteration and save the eyes wherever possible. METHODS: The study is a retrospective analysis of patients of ROM with and without brain involvement, who underwent minimal surgical management between March 2021 to March 2022 along with their follow-up. RESULTS: There were 184 eyes of 148 patients diagnosed with CAM. The mean age was 51.7 years with a male predominance of 103 (70%). All patients developed ROM following the COVID-19 infection and the duration between diagnosis of COVID-19 and ROM was 36 ± 23 days. 18 cases (12%) were bilateral. 76 eyes (41%) had no vision at the presentation. Imaging revealed paranasal sinus involvement (100%), orbital apex involvement (61%), cavernous sinus involvement (53%), and central nervous system (CNS) involvement (47%). All the patients (100%) were treated with systemic Liposomal amphotericin-B and sinus debridement. Endoscopic debridement of the orbital disease was performed in 45 (30.4%) cases, 15(8.1%) eyes underwent exenteration and were later rehabilitated with a customized ocular prosthesis, 103 (56%) eyes underwent transcutaneous retrobulbar amphotericin-B. At a mean follow-up of 13.1 months; the complete resolution was seen in 25 (17%) cases, the residual stable lesion was seen in 77(52%) of the cases and new lesions were developed in 13(9%) of the cases. Mortality was seen in 33 (22%) patients and all of them had CNS involvement. CONCLUSIONS: Systemic and protocol-based management can save the life and salvage the eyes.
ABSTRACT
This paper presents a method for evaluating the utility of deep transfer learning in the development of a classifier for detecting COVID-19 positive patients using CT scan images. Deep Learning (DL) is good at detecting COVID-19 cases, according to the research. For expanding the training dataset to reduce overfitting and improve the model's generalization capacity data augmentation approach is employed. The proposed study has evaluated a set of pretrained deep neural networks for Convolutional Neural Network (CNN). The suggested model used DenseNet with Res Net and a two-layer CNN model which gives better performance. The proposed model gives efficient results with the training and testing accuracy of 0.98 and 0.96. © 2022 IEEE.
ABSTRACT
Firms are using blockchain technology to prevent fraudulent activities through consensus mechanisms and help identify data tampering through its underlying characteristics, such as immutability, encryption transparency, and operational resilience. However, a holistic review of blockchain application in building a cyber-secure supply chain remains elusive, which can impede the advancement of the field when competing arguments are made, and pure replications are initiated. Therefore, the present study carries a systematic literature review to assess the state of literature review on the significance of blockchain in developing a cyber-secure and resilient supply chain. A systematic review of 122 peer-reviewed papers published between 2012 and 2022 has been conducted using a structured methodological approach. Further, the Theory, Context and Methodology (TCM) framework has been applied to suggest avenues for future research. Our analysis reveals six dominant themes related to blockchain and its adoption, blockchain application for resilience, blockchain application for cyber-security, blockchain and its role in intermediation, disintermediation and reintermediation, challenges of blockchain adoption and benefits of blockchain applications in the supply chain. Although the role of blockchain application in the cyber secure and resilient supply chain has been recognised, very little attention has been given to contextual factors affecting its adoption and consequences on key performance parameters. The present study contributes to the literature by synthesising the prime findings of reviewed papers and the managerial impli-cations, thereby giving a holistic view of the existing research and presenting an array of future opportunities for firms to adopt blockchain technology in the supply chain.
ABSTRACT
Objective: To evaluate clinical profiles of COVID-19 neonates and compare early onset (<7 days) vs late onset (>=7 days) COVID. Method(s): Prospective observational study conducted among the neonates who were at risk or COVID-19 positive and who were admitted consecutively in one year (from June 2020 to May 2021) to evaluate their clinical status. At risk neonates underwent RT-PCR for oropharyngeal swab within 24 to 48 hours of life (inborn) or after admission (outborn). Result(s): Out of 351 at risk neonates, 106 babies came positive (early = 35.4% and late = 64.6%). Twelve (11.3%) cases were positive within 24 to 48 hours of life, indicating perinatal transmission. A total of 62 (58.4%) positive newborns were symptomatic. In their clinical course, there was Respiratory distress in 33(31.1%), diarrhoea in 7 (6.6%), poor feeding or lethargy in 24 (23.1%), fever in 19 (17.9 %) neonates. One baby developed COVID MIS-N. Early onset group was more symptomatic (P value <.05) but late onset group had a longer hospital stay (Spearman's rho <0.5) and increased duration of oxygen requirement (t-test sig. [2-tailed] < 0.05). Conclusion(s): There is high incidence of perinatal transmission. Early onset group was more symptomatic but late onset group had increased duration of oxygen requirement and longer hospital stay. Copyright © 2022 National Neonatology Forum.
ABSTRACT
Carbon-based inorganic nanomaterials (CINMs) which include carbon nanotubes (CNTs), graphene quantum dots (GQDs), graphene (G), graphene oxide (GO), reduced graphene oxide (rGO), and mesoporous carbon nanoparticles (MCNPs) have gained significant interest in biomedical application. The unique geometries (i.e., dimensions: 0D, 1D, 2D, 3D), chemical functionality/surface chemistry, and tunable physical properties of the CINMs make more interesting materials for theranostic applications. These properties of CINMs endowed their use in the delivery of therapeutics (drug/gene/biomolecules) for therapy and diagnostics (imaging/tracking) as an agent for cells and tissue imaging. In this chapter, we will highlight the recent advancement of CINMs and their tunable structure for various drug delivery and optical properties for imaging cells and tissues using different imaging modalities. Furthermore, we will summarize the CINMs role and promising applications for theranostic applications in infectious diseases such as tuberculosis (TB), influenza (H1N1), Ebola virus disease (EVD), Middle East respiratory syndrome virus (MERS), severe acute respiratory syndrome coronavirus (SARS-CoV), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and other infectious diseases and also discuss the future perspectives to find the desirable platforms. © 2022 Elsevier Inc. All rights reserved.
ABSTRACT
Background: During the second wave of COVID-19, India suffered from a catastrophic outburst of cases and rapid transmission of disease due to the highly infectious delta strain (B.1.617.2). Patients infected with this strain underwent prolonged hospitalisations, suffered from severe symptoms. A sudden surge of fungal infections, primarily Mucormycosis was observed. Methods: We conducted a case-control study to study various risk factors and form of intracranial involvement in cases of Mucormycosis. Results: Study included 121 patients in total;out of which 61 were Mucormycosis patients with prior COVID-19 infection. 30 out of 61 Mucormycosis patients had intracranial involvement with majority having stroke in the form of the either infarct (10 patients, 34%);or haemorrhage (3 patients, 10%) and thrombosis of artery involvement (8 patients, 29%). Other intracranial form of involvement was abscess (6 patients, 20%) and meningitis (2 patients, 7%). The most frequent type of infarcts were lacunar infarcts and the most common location of infarcts were middle cerebral artery (MCA) or anterior cerebral artery (ACA). Patients were treated with administration of Amphotericin B and Posaconazole. Telephonic follow-up was conducted after a time period of about 90 days and their health condition was recorded on basis of modified ranking scale (mRS). Out of the 30 Mucormycosis infection patients displaying the occurrence of stroke, 10 patients could not survive. q Conclusion: Intracranial Mucormycosis in COVID19 patients presenting with stroke were observed frequently and had mortality in about one-third cases.
ABSTRACT
Background: The world was witness to a pandemic never experienced by this generation. The call to arms was answered by each branch of medicine, each fighting separate wars. The war, we as neurologists faced was the “Battle for the Vessels”. Health care workers are a precious resource in Low-Middle-Income-Countries. Hence, exposure to a covidpositive patient for a “full hour” during thrombolysis, isn't warranted. Hence Tenecteplase use which fits the bill “ideally” and “literally” was analysed in this study against Alteplase in strokes with covid-positivity. We analyse the factors which affect their action and the role covid had, in each scenario. Methods: This is an ambi-spective observational study of 37 patients in an apex tertiary-care centre in India. Routine stroke variables were assessed including follow-up imaging, functional outcomes at 3 months. The results were also analysed with the thrombolysis data from covidnegative individuals too in the same period. Results: Among the covid-positive patients 62.16% patients received tenecteplase while 37.83% received alteplase. Although the baseline characteristics were similar, the time-metrics for thrombolysis were significantly favourable in the tenecteplase arm. The median-hospital stay was shorter in the tenecteplase group as was the in-hospital mortality. On follow-up at 3 months, the median mRS-score was significantly favourable in the tenecteplase group. Conclusions: Thrombolysis during the pandemic has been a challenge in many ways especially in resource limited settings. This study shows that there needs to be a conscious and judicial transition towards tenecteplase during the pandemic, where healthcare workers are a precious resource too.
ABSTRACT
Present study was conducted in ABV Government Medical college, which was the only recognised covid hospital by Government of M.P., with tertiary care facilities in Vidisha district. This study is a record based cross sectional study done to determine various clinico-demographic profile and co-morbidities associated with mortality, among covid 19 patients who died after initiation of treatment in IPD. Mean age affected was 56.64 yrs with slight preponderance of males. Almost 64.22% patient who died were suffering from comorbidities in whom the common were hypertension (11%), diabetes mellitus (9.17%), coronary artery disease (11%), renal involvement (5.5%), obesity (4.58%) and respiratory involvement (8.25%) cases. Common signs and symptoms were fever (92%), cough and cold (90%), dyspnoea (84%), fatigue and myalgia (71%) cases. Oxygen saturation was below 80 mm of Hg in 23.8 % patients and mean duration of hospital stay hospital was 4.0 days. Respiratory support in the form of Bi-pap and C-pap was needed in 17.43% cases and endotracheal intubation was needed in 7.33% cases. Treatment of cardiogenic shock was given in 22.01% cases. © 2022
ABSTRACT
Purpose - The aim of this study is to examine the impact of supply chain management (SCM) practices and retail outlet attributes on the performance of organised food retailers in India during COVID-19 pandemic. Design/methodology/approach - Authors conducted empirical research with SCM practices and retail outlet attributes to evaluate the retailers performance. The authors present the results from 321 valid responses from the Indian food retailers. The study used structured equation modeling to present the analysis and the results. Findings - The findings of this study reveal that most of the SCM practices (i.e. information technology, level of information sharing, customer relationship, supplier relationship and goal congruence) have a positive impact on performance except the quality of information sharing. The results show that in the time of the pandemic, the retail outlet attributes (image, service quality and convenience) have no significant relationship with the food retailer's performance while SCM practices are necessary to achieve better performance of the food retailers. Research limitations/implications - A proactive approach is needed from retailers at the time of pandemic situations to manage the supply chains. The retailers must be extra careful in screening the suppliers for the short and long run. The reason being that in the situation of pandemic, customers might be more demanding and hence, food retailers need to pay special attention to gain growth. It is also required that the policymakers should give importance to the implementation of these SCM practices to be positioned differently. Originality/value - The research can be valued in terms of its original contribution towards companies in overcoming the disruption caused by COVID-19 to maintain a balance between demand and supply and proposes a completely new theoretical framework. The proposed theoretical model would add value to the existing literature to help the retailers in process of their performance improvement. The study has provided insights for retail organisations, suppliers and government departments to manage their SCs more effectively and efficiently during the pandemic.
ABSTRACT
Calling Covid-19 a viral disease would be an understatement. The worldwide impact this pandemic has caused in every sphere of human life is remarkable and so is the pace at which treatment modalities and immunisation agents were formulised for it. More so, the severe complications of this disease can be devastating and fatal, therefore a number of pharmaceutical agents have been studied that have shown response in the critically ill. This article throws light upon how melatonin can be a safe and effective adjuvant pharmaceutical agent against Covid-19. Melatonin is one of the hormones that controls the bodily clock, which in turn has a crucial role to play in the pathogenesis of Covid-19. Yoga asanas can also aid in suppressing the aggravated immune response and inflammatory process in this disease. Anxiety due to the disease itself and other social factors related to it, is another reason for disturbed sleep and hence poor immune response in alleviating the effects of Covid-19.
ABSTRACT
Aim: The aim of the present study assessment of new-onset depression and anxiety associated with COVID-19. Methods: This analytical, cross-sectional study was done the Department of Psychiatry Adesh Medical College Hospital Ambala Haryana, India for 10 months. By using Google Form platform contained validated online survey among Indian population which includes all adult males and females during or post COVID-19 infection and compared to the non-COVID-19 population as a control group. Results: 38% of participants were male while 62% are females. 26% of participants were married while 70% were single. 60% of participants are students and 38% are employed while 2% are retired. Regarding the COVID-19-positive and COVID-19-negative participants, 25% of participants reported having been diagnosed with COVID-19. Scores of PHQ-9 ranged from 0 to 27 (the mean is and the standard deviation is 6.12). Depression prevalence in our sample was 40%. Scores of GAD-7 ranged from 0 to 21 (the mean of 8.99 and the standard deviation is 5.33). Anxiety prevalence in our sample was 41%. The model shows a significant overall effect of gender [F(489) = 39.02, p<0.001], a non-significant effect of COVID-19 infection [F(489)=1.88, p=0.177] and a trending effect of the interaction between gender and COVID-19 [F(489) = 3.25, p=0.069]. Since the effect is not significant, we did not run any post hoc analyses. Conclusion: Significant levels of depression and anxiety were observed among the study population. The high levels of depression and anxiety may have masked the differences between those with or without COVID-19.
ABSTRACT
Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been predominately associated with respiratory illness. Acute kidney injury (AKI) is the most common reported kidney involvement. Kidney complications, including proteinuria, hematuria, and rarely collapsing glomerulopathy (CG), a form of focal segmental glomerulosclerosis (FSGS), are also well known now and are frequently documented in the literature published so far. We present two cases of glomerulonephritis (GN) in the setting of AKI in COVID-19 infection in children. Kidney biopsy specimens showed immunoglobulin A nephropathy (IgAN) with crescentic GN (CGN) with acute tubular injury with focal medium artery vasculitis. The patients exhibited a severe presentation and rapid progression to end-stage renal disease (ESRD). This report attempts to add a bit to the evolving information on COVID-19 disease, especially in children as far as kidney involvement is concerned.
ABSTRACT
Purpose The current study aims is to investigate the impact of leader's e-competencies on the emotional wellbeing of employees in GVTs. Also, the moderating role of a leader's emotional intelligence in enhancing the wellbeing of the employees during the pandemic was explored. Design/methodology/approach A survey of 810 employees belonging to international IT companies was conducted. The conceptual model was hypothesized and validated using CFA and PL-SEM. Findings The three core e-competencies of leaders (e-communication skills, e-change management skills and e-technological skills) impacting the wellbeing of employees in the COVID pandemic were found. Also, emotional intelligence significantly moderated the association of leader's e-competencies and the wellbeing of employees. Research limitations/implications The study is limited to IT sector companies. Data were collected using the snowball sampling technique through a self-reported questionnaire. Future studies can explore the relationship between e-leadership and variables like job performance in other sectors. Practical implications A unique framework of "leaders" e-competencies and employees' wellbeing, moderated by emotional intelligence, has been proposed and validated. The present study is relevant for guiding the traditional leaders and managers transitioning to e-leaders due to the pandemic. Originality/value The current exploration is one of its kinds to understand the dynamics of study variables in international workplaces. Today, the majority of organizations are conducting their business through GVTs. Therefore, the emerging leaders have to display specific e-competencies to contribute to employees' wellbeing effectively.
ABSTRACT
Local plant species have been in use in variety of ethnomedicinal practices from the time immemorial among the people of various communities for treating various human diseases. This paper reports about the plant species used by Adi community in curing various human diseases and ailments. A study was conducted during 2008-2009 and further refined in succeeding years with the 12 purposively selected traditional knowledge holders (TKHs) of Adi tribe of East Siang district, Arunachal Pradesh, India. Data were collected using combined approaches of personal interview, participant observations and transect walks. It was observed that with Shannon-Weaver diversity index 2.73, there were 39 local plant species belonging to 25 plant families and used as ethnomedicinal practices by the TKHs. Most of the species (17) were used by Adi TKHs with their green leaf parts followed by root and fruits (5 each) to develop ethnomedicinal formulations. Out of these, several species namely Leucas aspera (Willd.) Link.;Plumeria rubra L.;Catharanthus roseus (L.) G. Don;Solanum torvum Swartz;Solanum khasianum C.B. Clarke;Oroxylum indicum (L.) Benth.ex Kurze;and Tinospora cordifolia (Thunb.) (Miers) were found in use by Adis against asthma, bronchitis, cough, sinusitis, diabetes, malaria, typhoid and jaundice. The Adi TKHs maintain a rich cultural ethics, govern by their own world-view in continuing ethnomedicinal practices, and harvesting the species from various land use systems with the aim to sustain biodiversity and associated practices. The key findings indicated that, plant species used as ethnomedicines for some of the diseases and ailments by the Adi TKHs, can be undertaken for the long-term trial to find some natural remedies against few human diseases, including search of immune enhancer against COVID-19, provided TKHs of Adi community are partnered in ethically and culturally appropriate manner.