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1.
De Gruyter Handbook of Sustainable Development and Finance ; CHAP: 653-665,
Article in English | Scopus | ID: covidwho-2098839

ABSTRACT

Sustainable development, finance and related global policies and mechanisms have evolved over the decades. Today, regional initiatives for classifying sustainable activities exist, and several decades' research and development of ecosystem services and natural capital have identified and tested alternative economic models. The World Bank has the potential to finance them and sustainability at the landscape scale is achievable. But economic and environmental values can come into conflict. In developing countries, sustainable alternatives exist in business activities such as coastal and marine tourism. Financing small businesses through sound digital infrastructure is critical, as is the use of public fiscal instruments for the sustainable use of natural resources. Despite its developed status, renewable energy policies in the EU are leading to forest destruction. Financial vehicles such as green bonds have a similar potential. To avoid greenwashing, more focus needs to be on meeting the needs of those at the base of the economic pyramid, resourcing them with smart technologies and valuing civic engagement. Climate finance must be ethical and its allocation have integrity;this will foster community resilience. To avoid repeating the mistakes of terrestrial development, the world's oceans need to be protected and new business models adopted in this expanding frontier. Now is the time for all sectors to create a sustainable future for the planet and its inhabitants in the post-COVID, postcarbon era to come. © 2022 Walter de Gruyter GmbH, Berlin/Boston.

2.
De Gruyter Handbook of Sustainable Development and Finance ; CHAP: 329-348,
Article in English | Scopus | ID: covidwho-2098834

ABSTRACT

AI (artificial intelligence) and blockchain are promising technologies for all countries, including India. While these two technologies have a landscape of associated risks, there are distinct aspects like decentralisation and distribution, which make these technologies particularly suitable for India. It seems that the promise of technology could not come any sooner, especially as India faced the COVID-19 crisis in 2021. With this in mind, the chapter will do three things. First, the chapter will draw out a framework of effective risk management of AI and blockchain and put forward methods of effective decentralised decision-making. Second, the chapter will comment on the nature and sources of finance in this technology transition in India with empirical evidence. Third, the chapter will trace policy feedback and suggest a way forward with a focus on the COVID-19 crisis. Thus, the chapter will seek to draw out a meaningful narrative about the landscape of AI and blockchain in India particularly in its use to attain effective local governance and sustainable development. © 2022 Walter de Gruyter GmbH, Berlin/Boston.

3.
Journal of the American Academy of Child and Adolescent Psychiatry ; 61(10 Supplement):S93-S94, 2022.
Article in English | EMBASE | ID: covidwho-2076252

ABSTRACT

Objectives: This presentation will give an overview of the impact of sleep on physician burnout and wellness. We aim to discuss strategies to improve sleep among physicians. Method(s): A literature review was conducted to assess the available data. The audience will be engaged by utilizing polls throughout the presentation. Result(s): Multiple studies show that approximately 1 in 2 physicians, either in training or in practice, report burnout. Data also suggest that physicians sleep 6.5 hours on an average as compared to the recommended 8 hours. Nearly half of the practicing physicians attributed work schedules to poor sleep. Sleep deprivation is also attributed to the culture of medical training. COVID-19 has further added to the workload of physicians, resulting in reduced sleep. Poor sleep causes depletion of energy stores, contributing to burnout. Insufficient sleep can affect sleep architecture, worsen anxiety, increase stress, affect mental health, and thus result in burnout. Poor sleep can also cause fatigue and excessive daytime sleepiness, impair cognitive functioning, and contribute to burnout. The relationship between job-related stress, sleep, and burnout symptoms has been noted in different studies. The increased demand of child and adolescent psychiatrists secondary to the pandemic appears to contribute to poor sleep and increased stress, thus contributing to burnout. Different strategies can be used to help improve sleep among physicians, including mental health providers, to help improve the overall well-being of physicians. Changes can be made on a personal level and institutional level to help with improvement in sleep among physicians. Conclusion(s): Sleep and physician burnout are closely related. There is increased stress on mental health providers including child and adolescent psychiatry providers, even more so during the pandemic. Measures taken on personal and institutional levels will help with improvement of sleep disturbances and mitigate factors leading to an increase in burnout. SLP, WL Copyright © 2022

4.
European Journal of Molecular and Clinical Medicine ; 9(7):185-192, 2022.
Article in English | EMBASE | ID: covidwho-2058367

ABSTRACT

INTRODUCTION: Patients Infected with CORONA VIRUS- 2019 (COVID-19) showed changes in their platelet counts and Mean platelet volume (MPV). The present study was aimed to observe any association between lowered platelet counts with mean platelet volume (MPV) from the corana positive individuals. METHOD(S): It is a prospective study from 1-8-2020 to 30-9-2020 .Patients who presented with complaints of Fever, sore throat, body pains, cough, breathlessness, diarrhoea were evaluated at the triage area of the Hospital. Throat swab was taken and RT-PCR was done and only 200 confirmed cases were included in the study. Patient blood samples were collected and processed in SYSMAX 5 -part Haematology analyser in the Hospital Central Laboratory. The patients CBP, Platelet count and MPV were tabulated. RESULT(S): Out of 200 COVID-19 confirmed cases, the numbers of males were 145 (72.5%) and females 55 (27.5%). Most of the patients belonged to age group 50 years (25.5%), 60yrs age group (21%). The Maximum age in our study group was 80 years, minimum age was 19 years and mean age was 50 years. In our study it was noticed that Severe thrombocytopenia was seen in one patient with platelet count 38,000/muL,(0.5%), Moderate thrombocytopenia was seen in two patients(1%) and mild thrombocytopenia was seen in 12 (6%) cases. In our study only fifteen cases (7.5%) showed thrombocytopenia. The MPV for all fifteen cases were studied and MPV was in Range of 9.6- 11.8 fl. CONCLUSION(S): Low platelet count and high MPV are associated with disease severity. Platelet count is one of easy cheap method for the assessing the disease severity along with other parameters Copyright © 2022 Ubiquity Press. All rights reserved.

5.
Multimedia Tools and Applications ; : 1-25, 2022.
Article in English | EuropePMC | ID: covidwho-2034315

ABSTRACT

COVID-19 pandemic has a significant impact on the global health and daily lives of people living over the globe. Several initial tests are based on the detecting of the genetic material of the coronavirus, and they have a minimum detection rate with a time-consuming process. To overcome this issue, radiological images are recommended where chest X-rays (CXRs) are employed in the diagnostic process. This article introduces a new Multi-modal fusion of deep transfer learning (MMF-DTL) technique to classify COVID-19. The proposed MMF-DTL model involves three main processes, namely pre-processing, feature extraction, and classification. The MMF-DTL model uses three DL models namely VGG16, Inception v3, and ResNet 50 for feature extraction. Since a single modality would not be adequate to attain an effective detection rate, the integration of three approaches by the use of decision-based multimodal fusion increases the detection rate. So, a fusion of three DL models takes place to further improve the detection rate. Finally, a softmax classifier is employed for test images to a set of six different. A wide range of experimental result analyses is carried out on the Chest-X-Ray dataset. The proposed fusion model is found to be an effective tool for COVID-19 diagnosis using radiological images with the average sensy of 92.96%, specy of 98.54%, precn of 93.60%, accuy of 98.80%, Fscore of 93.26% and kappa of 91.86%.

6.
Journal of Cotton Research and Development ; 36(2):244-251, 2022.
Article in English | CAB Abstracts | ID: covidwho-2010741

ABSTRACT

The impact of COVID 19 on the economy in general is no doubt ravaging and its impact on agriculture is complex and varied across diverse segments that form the agricultural value chain. Cotton has a complex supply chain that stretch from input suppliers, farmers, traders, ginning factories, spinning mills, textile companies and oil processors. The study was designed to capture the panoramic view of world and national cotton economy during the pandemic period and its impact on cotton fanning in India. Cotton prices declined in the initial months for January to April, 2020 and later recouped once the lock down restrictions were phased out. As such from the study during the year 2020-2021, it was noticed in general, as per CAB estimates, cotton fanning in India was not Effected in its area and production excepting in north zone which was not due to lock down but for the pest attack and lack of irrigation facilities. Districtwise analysis confirmed that labour availability for loading and unloading and its transport was the major impediment especially in the southern zone while it was market uncertainty in the other zones. During the COVID 19 pandemic year, the cotton value chain, like others, had faced unprecedented disruptions. Cotton farmers and supply chain actors should work together to make sure that the farmers have secured acquaintance to sell their cotton. Farmers' protection should be considered a priority in getting the minimal requirements regarding the input supply, logistics and remuneration for their produce.

7.
Journal of Clinical Oncology ; 40(16), 2022.
Article in English | EMBASE | ID: covidwho-2009531

ABSTRACT

Background: Many hospitals have established goals-of-care (GOC) programs in response to the COVID- 19 pandemic;however, few have reported their outcomes. MD Anderson Cancer Center launched a multicomponent interdisciplinary GOC (myGOC) program in March 2020 that involved risk stratification, team huddles to discuss care planning, oncologist-initiated GOC discussions, communication training, palliative care involvement, rapid-response GOC team deployment, and daily monitoring with immediate feedback. We examined the impact of this myGOC program among medical inpatients. Methods: This single-center study with a quasi-experimental design included consecutive adult patients with cancer admitted to medical units at MD Anderson Cancer Center, Texas during an 8-month pre-implementation (May 1, 2019 to December 31, 2019) and post-implementation period (May 1, 2020 to December 31, 2020). The primary outcome was intensive care unit (ICU) mortality. Secondary outcomes included ICU length of stay, hospital mortality, and proportion/timing of patients with inhospital do-not-resuscitate (DNR) orders, medical power of attorney (MPOA), living will (LW) and outof- hospital DNR (OOHDNR). Propensity score weighting was used to adjust for differences in potential covariates, including age, sex, cancer diagnosis, race/ethnicity, and Sequential Organ Failure Assessment (SOFA) Score. With a sample size of 600 ICU patients over each time period and a baseline ICU mortality of 28%, we had 80% power to detect a 5% reduction in mortality using a two-tailed test at 5% significance level. Results: This study involved 12,941 hospitalized patients with cancer (Pre n = 6,977;Post n = 5,964) including 1365 ICU admissions (Pre n = 727;Post n = 638). After myGOC initiation, we observed a significant reduction in ICU mortality (28.2% vs. 21.9%;change -6.3%, 95% CI -9.6, -3.1;P = 0.0001). We also observed significant decreases in length of ICU stay (mean change -1.4 days, 95% CI -2.0, -0.7 days;P < 0.0001) and in-hospital mortality (7% vs. 6.1%, mean change -0.9%, 95% CI -1.5%, -0.3%;P = 0.004). The proportion of hospitalized patients with an inhospital DNR order increased significantly from 14.7% to 19.6% after implementation (odds ratio [OR] 1.4, 95% CI 1.3, 1.5;P < 0.0001) and DNR was established earlier (mean difference -3.0 d, 95% CI -3.9 d, -2.1 d;P < 0.0001). OOHDNR (OR 1.3, 95% CI 1.1, 1.6, P < 0.0007) also increased post-implementation but not MPOA and LW. MPOA, LW and OOHDNR were documented significantly earlier relative to the index hospitalization in the post-implementation period (P < 0.005 for all). Conclusions: This study showed improvement in hospital outcomes and care plan documentation after implementation of a system-wide, multicomponent GOC intervention. Our findings may have implications for GOC programs during the pandemic and beyond.

8.
Journal of General Internal Medicine ; 37:S254, 2022.
Article in English | EMBASE | ID: covidwho-1995620

ABSTRACT

BACKGROUND: Patients with mental illness have high COVID-19 infection rates and mortality. Equitable vaccination strategies have prioritized outreach for high-risk medical conditions, racial/ethnic groups, and social groups (e.g., experiencing homelessness). Despite calls to ensure adequate access for persons with mental illness, COVID-19 vaccination disparities have not been systematically evaluated in this population. A recent study demonstrated that Veteran's Administration (VA) systems can deliver equitable vaccine access for traditionally marginalized racial/ethnic groups.We sought to evaluate whether there are disparities in COVID-19 vaccination rates for veterans with mental illness. METHODS: We conducted a retrospective cohort study among Veterans assigned to primary care at the VA Puget Sound with >1 visit recorded in the past two years. We used logistic regression to determine the association between diagnosis of serious mental illness (SMI) (bipolar disorder or schizophrenia), post-traumatic stress disorder (PTSD), depression or anxiety, and substance use disorder (SUD) and COVID-19 vaccination using three separate models. Covariates were age, sex, race/ethnicity, marital status, Gagne comorbidity score, socioeconomic status index, rurality based on home address, homelessness, number of primary care and mental health visits in the past 12 months, and percentage without a high school degree. RESULTS: We identified 103,025 veterans with no mental health diagnoses, 1,467 with SMI, 15,329 with PTSD, depression or anxiety, and 5,110 with SUD. Those with mental health diagnoses were younger, had higher Gagne scores, higher primary care and mental health utilization, were more likely to experience homelessness, and to live in urban settings. In adjusted analysis the odds ratio of vaccine receipt was higher in all three groups compared to those without mental health diagnoses: 1.58 (95% CI 1.38, 1.82) for SMI, 1.26 (1.2, 1.32) for PTSD/Depression/Anxiety, and 1.24 (1.15, 1.34) for SUD. CONCLUSIONS: After adjusting for clinical and sociodemographic covariates, we found that diagnoses of SMI, SUD, PTSD, depression or anxiety were associated with a slightly higher predicted probability of vaccination compared to no mental health diagnoses among Veterans receiving primary care within the VA. No other published analysis reports vaccination rates in persons with mental health conditions, so we are unable to assess whether this is a trend nationally or specific to the VA system, where vaccination efforts were conducted using a clear equity framework, strong data sources, and heavy outreach campaigns. Study limitations include unclear generalizability to other geographic areas, and exclusion of veterans with mental health diagnoses not enrolled in primary care, due to lack of adequate clinical covariate information. Nevertheless, our results provide initial evidence that disparities in COVID-19 vaccination rates for persons with mental illness can be prevented.

9.
J Orthop ; 34: 8-13, 2022.
Article in English | MEDLINE | ID: covidwho-1966872

ABSTRACT

Purpose: This study aimed to audit the effects of vitamin D3 on the early functional outcomes, the incidence of nosocomial COVID-19 infection and complications in patients undergoing elective Total Knee Arthroplasty (TKA). Methods: This was a retrospective study involving patients undergoing primary unilateral TKA between January 2020 to May 2021 operated by a single surgeon using a single implant. Participants were divided into two cohorts, Deficient-vitamin D3 level <20 ng/ml and Sufficient-vitamin D3 level ≥20 ng/ml. Assessment for Knee Society Score and Oxford Knee Score (OKS) was done preoperatively and one year after TKA. Nosocomial COVID-19 infection rate, 30-day re-admissions and complications were noted during the study. Results: 235 patients were divided into 2 cohorts matched by age, gender and ASA grades. 74 patients belonged to the deficient group and 161 belonged to the sufficient group. The mean preoperative scores in the sufficient group were higher than the deficient group (OKS = 15.74 vs 12.95; KSS = 88.91vs 85.62). Similarly, the one-year postoperative scores in the sufficient group were significantly higher (OKS = 36.54 vs 35.16; KSS = 164.01 vs 161.22). A linear correlation was present between preoperative score (r = 0.273) & post-operative scores (r = 0.141) with serum vitamin D3 levels. Vitamin D3 deficient individuals had higher nosocomial COVID-19 infection rate (10.81% vs 4.96%,p = 0.16). The incidence of complications like DVT, embolism, stroke, infection and fracture were not statistically different in the two groups. Conclusion: Vitamin D positively influences the outcomes of TKA and protects against nosocomial COVID-19 infection in patients undergoing elective TKA.

10.
8th International Conference on Advanced Computing and Communication Systems, ICACCS 2022 ; : 91-96, 2022.
Article in English | Scopus | ID: covidwho-1922634

ABSTRACT

During the period of prevailing unsettled COVID pandemic, the countries and states started to plan reopening during which necessitates the non-contact temperature evaluation gadgets as a part of a preliminary look at access points to identify the humans with elevated body temperatures. Despite the utilization of these devices, temperature assessment restricted the impact on lowering the spread of COVID-19. Non-contact temperature measuring devices are used to measure the temperature of any person. Detection of a high temperature is one huge manner to pick out a person who might also have COVID-19 contamination. In this project, a room environment is created in which certain precautions are taken. A laser diode and receiver are used to detect the entrance of a person, and the system also detects the body temperature of the entering person. If the temperature is less than a threshold temperature entry for the person is permitted or else the entry is denied. This system also has a feature where it permits only a pre-determined number of persons inside the room. It also facilities to view the allowed temperature, the number of people to be allowed in the room and the number of people present actively using a Bluetooth App. This system aimed to be useful to combat the spread of COVID infections. © 2022 IEEE.

11.
8th IEEE Asia-Pacific Conference on Computer Science and Data Engineering (IEEE CSDE) ; 2021.
Article in English | Web of Science | ID: covidwho-1895887

ABSTRACT

The rise of the Coronavirus pandemic was unanticipated, and it turned into a very serious and catastrophically dangerous scenario especially in terms of financial balance, physical and mental health, population growth, socialization, and globalization. This paper considers Australian COVID-19 data from its beginning on the 25th of January to this date for experimental study. The popular Microsoft Power BI tool and Python coding language were primarily utilized to visualize the data sets and understand the depth of the COVID-19 situation in Australia. More specifically Python is primarily used in this study on the data to generate visualizations and forecasted models for effective interpretation of the ongoing medical peril. The plots and graphs created significantly extract trends for the accumulative infection rates ongoing in Australia from February 2020 to September 2021. Such important comprehensions of the numerical data set allowed for a graphical understanding and representation with data science applications. Statistical forecasting models such as the autoregressive integrated moving average (ARIMA) model and the long short-term memory (LSTM) model were applied to the time series data of Australian COVID-19 infection numbers to predict the future trends of COVID-19 cases in Australia. Finally, we feel this research can help the policymakers and health practitioners to manage such global medical issues more efficiently in the future with the help of data science technology and applications which is the uprising heart of our technological era.

12.
Topics in Antiviral Medicine ; 30(1 SUPPL):55, 2022.
Article in English | EMBASE | ID: covidwho-1880940

ABSTRACT

Background: The number of undiagnosed persons globally remains a barrier to achieving UNAIDS 95-95-95 goals. While nearly 80% are aware of their status, there is much variability by age and geography. Many of those undiagnosed are not engaging in traditional HIV services and do not visit physical locations;novel strategies are needed to overcome structural barriers. We implemented an online, HIV self-testing (HIVST) service for vulnerable populations in India. Methods: An integrated web-based platform for HIVST www.safezindagi. net/selftesting was implemented across 24 Indian states in July 2021. Virtual outreach workers (vORWs) contacted clients on dating apps and social media platforms, provided counseling, and directed interested clients to HIVST via a platform that allowed for home delivery or pick up at a community site. HIVST could be assisted or unassisted with pre/post-test counseling from vORWS. Linkage to confirmatory testing/ART and PrEP was provided as needed. Descriptive statistics were used to characterize outcomes. Results: Between June 30-October 21, 2021, 2,234 clients registered and 1,356 (61%) clients ordered an HIVST kit. Median age of the 1,356 clients was 27 years;74% were male and 66% self-identified as MSM. Ten percent self-identified as transgender. In the prior 6 months, 67% reported condomless sex, 51% multiple partners, 13% transactional sex, 7% STIs, and 4% injection drug use. 1,190 clients (88%) received their kits within 3 days;44% used a courier service and 56% picked up from a community site. Of 1,070 (90%) results uploaded, 43 (4%) were positive with geographical variability (5 states had >4% positivity). The median age of the positive clients was 30 years and 74% were male. Of importance, 65% reported condomless sex with multiple partners in prior 6 months and none were previously tested for HIV. 19 (44%) were linked to confirmatory testing of whom 16 (84%) were confirmed positive and 14 (88%) initiated ART at public centers (see Figure). Conclusion: These data highlight the role of an HIVST platform to reach first time test-takers in a population with high risk behaviors and identified HIV burden >16 times the general population. With increasing online engagement and uptake of telemedicine globally, as well as continuing disruptions due to COVID-19, HIVST offers a critical approach to reach high-risk individuals, identify PLHIV, and link them to care and treatment.

13.
American Journal of Respiratory and Critical Care Medicine ; 205:2, 2022.
Article in English | English Web of Science | ID: covidwho-1879995
14.
1st International Conference on Technologies for Smart Green Connected Society 2021, ICTSGS 2021 ; 107:1649-1662, 2022.
Article in English | Scopus | ID: covidwho-1874756

ABSTRACT

After the most recent Covid-19 outbreak, which has now made headlines, people trace back the connections of SARS-CoV-2 virus with other recent outbreaks such as SARS, MERS, Avian influenza, etc all of which have high virulence and destructive powers. The common feature observed in all these alarming outbreaks is that they are “Zoonotic spillover diseases.” Spillover event also referred to as spillover infection or simply pathogen spillover is the process where a pathogen jumps from an animal to a human. Despite posing a threat to public health worldwide, it is an inadequately understood phenomenon. Modeling the behavior of zoonotic pandemic while taking epidemiological, ecological and behavioral determinants of pathogen exposure into consideration plays a vital role in its control. Interventions can be designed based on these models to reduce or eliminate the risk of spillover, hence preventing epidemics or devising better strategies to fight them in the future. © The Electrochemical Society

15.
NeuroQuantology ; 20(4):325-336, 2022.
Article in English | EMBASE | ID: covidwho-1863396

ABSTRACT

In the recent past, mental health has become a global concern. COVID-19 has further caused a rapid surge in depression. Depression is a serious mental illness that is impacting the lives of individuals of all ages all around the world. Depression affects a person's physiological well-being as well as their emotional state. Now days, Depression is the most common element experienced by the human beings irrespective of their age factor and professional life. To detect the depression status among the persons, the system uses different approaches by using the sensor technology. The automatic identification of depression at early stages or immediately helps the clinical studies to cure the people accurately. In this proposed research, the system aims to identify the depression using facial expressions, voice, live video capturing, by analysing their tweets, status, posts in the social media. By applying computer vision integrated with ML and DL techniques, the entire capturing and analysis process gets automated and the complexity involved in the model designing gets reduced because the system focuses more on extracting the statistical features involved in movements and behaviour of the human being. Most of the existing research works focuses on the unimodal development which focuses on the single component analysis but the proposed research aims to focus on the multi modal with a fusion of different modalities of learning approaches involved in detection of depression, this survey provides an overview of numerous methodologies that have been created with the goal of employing emotion recognition to analyse depression.

16.
Journal of the American College of Cardiology ; 79(9):2089-2089, 2022.
Article in English | Web of Science | ID: covidwho-1849430
17.
Journal of the American College of Cardiology ; 79(9):2275-2275, 2022.
Article in English | Web of Science | ID: covidwho-1848688
18.
Current Science (00113891) ; 122(7):766-767, 2022.
Article in English | Academic Search Complete | ID: covidwho-1824355

ABSTRACT

The article focuses on export led growth for agriculture.

19.
2021 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1794854

ABSTRACT

The rise of the Coronavirus pandemic was unanticipated, and it turned into a very serious and catastrophically dangerous scenario especially in terms of financial balance, physical and mental health, population growth, socialization, and globalization. This paper considers Australian COVID-19 data from its beginning on the 25th of January to this date for experimental study. The popular Microsoft Power BI tool and Python coding language were primarily utilized to visualize the data sets and understand the depth of the COVID-19 situation in Australia. More specifically Python is primarily used in this study on the data to generate visualizations and forecasted models for effective interpretation of the ongoing medical peril. The plots and graphs created significantly extract trends for the accumulative infection rates ongoing in Australia from February 2020 to September 2021. Such important comprehensions of the numerical data set allowed for a graphical understanding and representation with data science applications. Statistical forecasting models such as the autoregressive integrated moving average (ARIMA) model and the long short-term memory (LSTM) model were applied to the time series data of Australian COVID-19 infection numbers to predict the future trends of COVID-19 cases in Australia. Finally, we feel this research can help the policymakers and health practitioners to manage such global medical issues more efficiently in the future with the help of data science technology and applications which is the uprising heart of our technological era. © IEEE 2022.

20.
Contrast Media Mol Imaging ; 2022: 7377502, 2022.
Article in English | MEDLINE | ID: covidwho-1741725

ABSTRACT

Coronavirus disease (COVID-19) is a viral infection caused by SARS-CoV-2. The modalities such as computed tomography (CT) have been successfully utilized for the early stage diagnosis of COVID-19 infected patients. Recently, many researchers have utilized deep learning models for the automated screening of COVID-19 suspected cases. An ensemble deep learning and Internet of Things (IoT) based framework is proposed for screening of COVID-19 suspected cases. Three well-known pretrained deep learning models are ensembled. The medical IoT devices are utilized to collect the CT scans, and automated diagnoses are performed on IoT servers. The proposed framework is compared with thirteen competitive models over a four-class dataset. Experimental results reveal that the proposed ensembled deep learning model yielded 98.98% accuracy. Moreover, the model outperforms all competitive models in terms of other performance metrics achieving 98.56% precision, 98.58% recall, 98.75% F-score, and 98.57% AUC. Therefore, the proposed framework can improve the acceleration of COVID-19 diagnosis.


Subject(s)
COVID-19 Testing , COVID-19/diagnostic imaging , Neural Networks, Computer , SARS-CoV-2 , Tomography, X-Ray Computed , Female , Humans , Male
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