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1.
Journal of Infectious Diseases ; 02:02, 2022.
Article in English | MEDLINE | ID: covidwho-2017959

ABSTRACT

There is limited evidence on vaccine effectiveness against asymptomatic or mild Omicron infections. We estimated that recent third doses of mRNA or inactivated vaccines reduced the risk of self-reported infection by 52% (95% confidence interval: 17%-73%), among randomly sampled adults during the Omicron BA.2 dominated surge in Hong Kong.

2.
Anatomical Sciences Education ; 06:06, 2022.
Article in English | MEDLINE | ID: covidwho-2013360

ABSTRACT

The coronavirus disease 2019 (Covid-19) pandemic has induced multifaceted changes in anatomical education. There has been a significant increase in the employment of digital technologies coupled with the upskilling of educators' capacity and altered attitudes towards the digitalization process. While challenges remain, learners have demonstrated capabilities to adapt to digital delivery, engagement and assessment. With alternative and innovative teaching and learning strategies having been trialed and implemented for almost two years, the key question now is what the pedagogy will be for anatomy education beyond the pandemic. Here we discuss some of the changes in anatomy education that have taken place as a result of the Covid-19 pandemic and importantly present some outlooks for evidence-based anatomy pedagogy as the world enters the post-pandemic phase and beyond. The authors conclude that the anatomy discipline is ready to further modernize and has the opportunity to use digital technologies to evolve and enhance anatomy education to ensure students are provided with the learning experience which will prepare them best for the future.

3.
Journal of Clinical Oncology ; 40(16), 2022.
Article in English | EMBASE | ID: covidwho-2005696

ABSTRACT

Background: To evaluate the efficacy and safety of different treatment modalities of regorafenib in patients with previously treated metastatic colorectal cancer (mCRC) in the real-world setting. Methods: Individual patient data were retrieved from three leading oncology centers in China from January 2016 to March 2021. The primary endpoint was progression-free survival (PFS), and secondary endpoints were overall survival (OS) and safety. Results: The characteristics of patients who received treatment are shown in the table. Twenty-one patients received regorafenib combined with capecitabine as the second-line treatment for those who cannot visit hospital for their chemotherapies because of the COVID-19 pandemic. The median PFS and median OS were 8 (95% CI 4.36 -11.00) months and 26.9 (95%CI 20.54 -NR) months. 101 patients received regorafenib and 69 patients received regorafenib plus immune checkpoint inhibitor (ICIs) as third or higher line treatment, the overall response was 4.1%(7/170), including one complete response. Patients combined with ICIs have longer PFS than those with regorafenib monotherapy (median PFS = 3.3 versus 2.1 months;p = 0.01). Starting dose was 80, 120 and 160 mg in 64, 40 and 39 patients, respectively. Dose reduction was observed in 43.3% (39/79) of patients receiving 120 and 160 mg as the initial dose. Conclusions: Different treatment modalities of regorafenib all showed promising efficacy and safety in the treatment of mCRC. Regorafenib combination is better than regorafenib monotherapy. Regorafenib combined with capecitabine provided a new treatment strategy during the epidemic but requires further investigation.

4.
Health and Place ; 77, 2022.
Article in English | EMBASE | ID: covidwho-2004102

ABSTRACT

Tackling mental health has become a priority for governments around the world because it influences not only individuals but also the whole society. As people spend a majority of their time (i.e., around 90%) in buildings, it is pivotal to understand the relationship between built environment and mental health, particularly during COVID-19 when people have experienced recurrent local and national lockdowns. Despite the demonstration by previous research that the design of the built environment can affect mental health, it is not clear if the same influence pattern remains when a ‘black swan’ event (e.g., COVID-19) occurs. To this end, we performed logistic regression and hierarchical regression analyses to examine the relationship between built environment and mental health utilising a data sample from the United Kingdom (UK) residents during the COVID-19 lockdown while considering their social demographics. Our results show that compared with depression and anxiety, people were more likely to feel stressed during the lockdown period. Furthermore, general house type, home workspace, and neighbourhood environment and amenity were identified to have significantly contributed to their mental health status. With the ensuing implications, this study represents one of the first to inform policymakers and built environment design professionals of how built environment should be designed to accommodate features that could mitigate mental health problems in any future crisis. As such, it contributes to the body of knowledge of built environment planning by considering mental health during the COVID-19 lockdown.

5.
Nat Chem Biol ; 2022.
Article in English | PubMed | ID: covidwho-1991635

ABSTRACT

The E3 ligase TRIM7 has emerged as a critical player in viral infection and pathogenesis. However, the mechanism governing the TRIM7-substrate association remains to be defined. Here we report the crystal structures of TRIM7 in complex with 2C peptides of human enterovirus. Structure-guided studies reveal the C-terminal glutamine residue of 2C as the primary determinant for TRIM7 binding. Leveraged by this finding, we identify norovirus and SARS-CoV-2 proteins, and physiological proteins, as new TRIM7 substrates. Crystal structures of TRIM7 in complex with multiple peptides derived from SARS-CoV-2 proteins display the same glutamine-end recognition mode. Furthermore, TRIM7 could trigger the ubiquitination and degradation of these substrates, possibly representing a new Gln/C-degron pathway. Together, these findings unveil a common recognition mode by TRIM7, providing the foundation for further mechanistic characterization of antiviral and cellular functions of TRIM7.

6.
International Journal of Contemporary Hospitality Management ; 2022.
Article in English | Scopus | ID: covidwho-1901354

ABSTRACT

Purpose: The airline industry has been one of the hardest-hit industries during the Corona Virus Disease 2019 (COVID-19) pandemic. This study aims to examine which flight attendants are likely to positively reappraise job insecurity and subsequently elevate their performance during the COVID-19 pandemic. Design/methodology/approach: A two-wave (i.e. Time 1 and Time 2), multi-source (i.e. flight attendants and chief flight attendants) survey was conducted. The final sample consists of 408 flight attendants matched with 57 chief flight attendants. Hierarchical linear modeling was used to test the hypotheses. Findings: Flight attendants with an organization-centered career orientation are likely to positively reappraise job insecurity and, in turn, have better job performance than those with a self-centered career orientation. Originality/value: Flight attendants are likely to experience job insecurity during the COVID-19 crisis. This study highlights a potential positive coping mechanism that is contingent upon flight attendants’ career orientations, facilitating the interaction of the stress-coping and vocational literature in a hospitality context. © 2022, Emerald Publishing Limited.

7.
Journal of Pacific Rim Psychology ; 16:12, 2022.
Article in English | Web of Science | ID: covidwho-1896301

ABSTRACT

The sudden outbreak of COVID-19 has exerted a tremendous impact on the psyche of people around the world, especially adolescents. In order to provide a valuable theoretical basis for effective measures to prevent psychological problems in adolescents during public health emergencies in the future, this study examined the mediating effect of coping style (CS, including positive coping style (PCS) and negative coping style (NCS)) and the moderating effect of emotional management ability (EMA) on the relationship between the psychological stress response (PSR) and aggression (AGG) in adolescents during the COVID-19 epidemic in China. The Buss-Warren Aggression Questionnaire, Simplified Coping Style Questionnaire, and Emotion Management Questionnaire were employed to investigate the mental health of Chinese adolescents from April 10-20 (Time point 1, T1) and May 20-30 (Time point 2, T2), 2020. A total of 1,931 adolescents (aged 10-25 years, M = 19.18 years, 51.4% male) were examined at T1 and 334 adolescents (aged 11-25 years, M = 19.97 years, 48.7% male) were reinvestigated at T2. Overall, 17.6% of the participants at T1 and 16.8% at T2 reported obvious PSR activation. NCS partly mediated the relationship between the PSR and AGG, and the indirect effect was moderated by EMA reported at T2. There were regional differences in the moderated mediation model in low-risk areas at T1. The moderated effects of EMA at T1 and T2 were opposite. Specifically, high EMA resulted in a stronger relationship between NCS and AGG at T1, whereas high EMA resulted in a weaker relationship between NCS and AGG at T2. Psychological reactions resulting from sudden public health events may trigger AGG in younger individuals. However, EMA may have a buffering effect on the onset of AGG. This research expands our understanding of the development of AGG in adolescents during the pandemic.

8.
Topics in Antiviral Medicine ; 30(1 SUPPL):378-379, 2022.
Article in English | EMBASE | ID: covidwho-1880068

ABSTRACT

Background: COVID-19 has caused severe disruptions in healthcare access. The impact on persons with HIV (PWH), including their outcomes along the HIV care continuum is still being assessed. Washington, DC is a hotspot for both HIV and COVID-19 infections. We sought to describe the impact of COVID-19 on the care continuum among a cohort of PWH enrolled in a longitudinal HIV study, the DC Cohort. Methods: DC Cohort participants enrolled by 09/1/2018 and active as of 3/1/2020 were included in the analysis (N=8,274). Using cross-sectional and longitudinal approaches, we assessed engagement in care (EIC) (i.e., at least one viral load [VL], CD4 or visit), receipt of cART, and viral suppression (VS)(i.e., VL<200 copies/ml) during the pre-pandemic era (3/1/2019-3/1/2020) versus the recent peri-pandemic era (9/1/2020-9/1/2021) using Cohort data. A subset of participant data was linked to a cross-sectional COVID-19 survey (N=801). Uni-and bivariate analysis were used to describe care continuum outcomes and factors associated with care disruption. Results: Among 8,274 participants, engagement in care during the pre (71.0%) vs peri pandemic (62.5%) era declined significantly (p<.0001). The proportion of participants who were on cART during each era was stable (90.9% vs 90.8% respectively, p=0.1131). 70.3% of participants achieved VS in the pre pandemic era vs 61.2% in the peri-pandemic era (p<.0001). Longitudinally, 9.5% of participants were no longer EIC peri-pandemic;2.4% of participants were no longer on cART peri-pandemic, 6.5% had a loss of VS and 7.3% had no labs in the peri-pandemic era. Among the subset of participants completing the survey, there were no significant differences between those who maintained VS versus those who did not/had no labs in demographics, employment, changes in income, insurance or housing, or self-reported ability to access non-HIV related care or telehealth. Most surveyed participants reported no change in their ability to fill ARV prescriptions (86%) or daily ARV adherence (89%);however, 20% and 13% reported decreased ability to make and keep HIV appointments, respectively, and 15% reported decreased ability to get laboratory examinations completed. Conclusion: Our analysis shows that COVID-19 has disrupted HIV care continuum outcomes including EIC, ART, and loss of viral suppression. As the pandemic continues, efforts to engage PWH through telehealth, multi-month dispensing, and home-based testing, are needed to ensure continued progress towards ending the HIV epidemic.

9.
The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences ; XLIII-B4-2022:195-202, 2022.
Article in English | ProQuest Central | ID: covidwho-1876035

ABSTRACT

The COVID-19 epidemic has posed a grave threat to human life. The stay-at-home quarantine is an effective method of minimizing physical contact and the risk of COVID-19 transmission. However, the supply of living materials (such as meat, vegetables, grain, and oil) has become a great challenge as residents' activities have been restricted. In this paper, we present a spatial analysis framework for the supply of living materials during COVID-19 outbreak by coupling an infectious disease model with geographic information system (GIS). First, a virus spreading spatial simulation model is developed by combining cellular automata (CA) and Susceptible-Exposed-Infected-Recovered-Death (SEIRD) to estimate COVID-19's spreading under various scenarios. Second, the demand and supply of living materials in the impacted residents are calculated. Finally, the imbalance of the supply and demand of the living materials is assessed. We conduct experiments in Shenzhen. The experimental results show that localities with supply-demand mismatches are primarily concentrated in the southwest of Bao'an District, the southern of Longhua District, and Longgang District. Additionally, the spatial distribution of the mismatch level between supply and demand for living materials in Shenzhen exhibits a significant agglomeration effect, manifested as "low-low" and "high-high" agglomeration. The spatial agglomeration effect of material mismatch has increased with the spread of the epidemic. These results support the prevention and control of the COVID-19 spreading.

10.
Zhonghua Yu Fang Yi Xue Za Zhi ; 56(4): 474-478, 2022 Apr 06.
Article in Chinese | MEDLINE | ID: covidwho-1834947

ABSTRACT

Objective: To analyze the course of disease and epidemiological parameters of COVID-19 and provide evidence for making prevention and control strategies. Methods: To display the distribution of course of disease of the infectors who had close contacts with COVID-19 cases from January 1 to March 15, 2020 in Guangdong Provincial, the models of Lognormal, Weibull and gamma distribution were applied. A descriptive analysis was conducted on the basic characteristics and epidemiological parameters of course of disease. Results: In total, 515 of 11 580 close contacts were infected, with an attack rate about 4.4%, including 449 confirmed cases and 66 asymptomatic cases. Lognormal distribution was fitting best for latent period, incubation period, pre-symptomatic infection period of confirmed cases and infection period of asymptomatic cases; Gamma distribution was fitting best for infectious period and clinical symptom period of confirmed cases; Weibull distribution was fitting best for latent period of asymptomatic cases. The latent period, incubation period, pre-symptomatic infection period, infectious period and clinical symptoms period of confirmed cases were 4.50 (95%CI:3.86-5.13) days, 5.12 (95%CI:4.63-5.62) days, 0.87 (95%CI:0.67-1.07) days, 11.89 (95%CI:9.81-13.98) days and 22.00 (95%CI:21.24-22.77) days, respectively. The latent period and infectious period of asymptomatic cases were 8.88 (95%CI:6.89-10.86) days and 6.18 (95%CI:1.89-10.47) days, respectively. Conclusion: The estimated course of COVID-19 and related epidemiological parameters are similar to the existing data.


Subject(s)
COVID-19 , Contact Tracing , Cohort Studies , Humans , Incidence , Prospective Studies
11.
Embase; 2022.
Preprint in English | EMBASE | ID: ppcovidwho-334805

ABSTRACT

Omicron sub-lineage BA.2 has rapidly surged globally, accounting for over 60% of recent SARS-CoV-2 infections. Newly acquired RBD mutations and high transmission advantage over BA.1 urge the investigation of BA.2's immune evasion capability. Here, we show that BA.2 causes strong neutralization resistance, comparable to BA.1, in vaccinated individuals' plasma. However, BA.2 displays more severe antibody evasion in BA.1 convalescents, and most prominently, in vaccinated SARS convalescents' plasma, suggesting a substantial antigenicity difference between BA.2 and BA.1. To specify, we determined the escaping mutation profiles1,2 of 714 SARS-CoV-2 RBD neutralizing antibodies, including 241 broad sarbecovirus neutralizing antibodies isolated from SARS convalescents, and measured their neutralization efficacy against BA.1, BA.1.1, BA.2. Importantly, BA.2 specifically induces large-scale escape of BA.1/BA.1.1effective broad sarbecovirus neutralizing antibodies via novel mutations T376A, D405N, and R408S. These sites were highly conserved across sarbecoviruses, suggesting that Omicron BA.2 arose from immune pressure selection instead of zoonotic spillover. Moreover, BA.2 reduces the efficacy of S309 (Sotrovimab)3,4 and broad sarbecovirus neutralizing antibodies targeting the similar epitope region, including BD55-5840. Structural comparisons of BD55-5840 in complexes with BA.1 and BA.2 spike suggest that BA.2 could hinder antibody binding through S371F-induced N343-glycan displacement. Intriguingly, the absence of G446S mutation in BA.2 enabled a proportion of 440-449 linear epitope targeting antibodies to retain neutralizing efficacy, including COV2-2130 (Cilgavimab)5. Together, we showed that BA.2 exhibits distinct antigenicity compared to BA.1 and provided a comprehensive profile of SARS-CoV-2 antibody escaping mutations. Our study offers critical insights into the humoral immune evading mechanism of current and future variants.

12.
The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences ; XLVI-3/W1-2022:15-20, 2022.
Article in English | ProQuest Central | ID: covidwho-1811068

ABSTRACT

Together with rapid development of location-based services and big-data platforms especially in urban areas, huge amount of spatiotemporal data are collected without properly used;on the other hand, state-of-the-art quantitative policy effect assessment techniques usually require panel data as input. To solve both issues, this paper follows the following approach: obtaining panel data by aggregating spatiotemporal data and feeding them to the effect assessment module. With the help of high-performance computing techniques which are able to deal with huge amount of data, we build framework Aggr-analysis which applies clustering algorithms to shrink the raw data set and find associations between different data sets via co-location analysis. Finally, we prove the effectiveness by an example: analysis of resident activities during the COVID-19 Pandemic. We apply Aggr-analysis to process the share-bike usage data and POI (Point Of Interest) data in Beijing, then obtain the panel data required by DID (Difference-in-Differences) method. Supplemented with environmental data, we conclude the net effect of the COVID-19 breakout on society and economy - the pandemic has reduced the overall resident mobility by 64.8% within two months.

13.
Zhonghua Liu Xing Bing Xue Za Zhi ; 43(4): 466-477, 2022 Apr 10.
Article in Chinese | MEDLINE | ID: covidwho-1810386

ABSTRACT

The COVID-19 pandemic is still ongoing in the world, the risk of COVID-19 spread from other countries or in the country will exist for a long term in China. In the routine prevention and control phase, a number of local COVID-19 epidemics have occurred in China, most COVID-19 cases were sporadic ones, but a few case clusters or outbreaks were reported. Winter and spring were the seasons with high incidences of the epidemics; border and port cities had higher risk for outbreaks. Active surveillance in key populations was an effective way for the early detection of the epidemics. Through a series of comprehensive prevention and control measures, including mass nucleic acid screening, close contact tracing and isolation, classified management of areas and groups at risk, wider social distancing and strict travel management, the local COVID-19 epidemics have been quickly and effectively controlled. The experiences obtained in the control of the local epidemics would benefit the routine prevention and control of COVID-19 in China. The occurrence of a series of COVID-19 case clusters or outbreaks has revealed the weakness or deficiencies in the COVID-19 prevention and control in China, so this paper suggests some measures for the improvement of the future prevention and control of COVID-19.


Subject(s)
COVID-19 , Epidemics , COVID-19/epidemiology , COVID-19/prevention & control , China/epidemiology , Contact Tracing , Epidemics/prevention & control , Humans , Pandemics/prevention & control , SARS-CoV-2
14.
PubMed; 2020.
Preprint in English | PubMed | ID: ppcovidwho-333560

ABSTRACT

Coagulopathy is associated with both inflammation and infection, including infection with the novel SARS-CoV-2 (COVID-19). Endothelial cells (ECs) fine tune hemostasis via cAMP-mediated secretion of von Willebrand factor (vWF), which promote the process of clot formation. The e xchange p rotein directly a ctivated by c AMP (EPAC) is a ubiquitously expressed intracellular cAMP receptor that plays a key role in stabilizing ECs and suppressing inflammation. To assess whether EPAC could regulate vWF release during inflammation, we utilized our EPAC1 -null mouse model and revealed an increased secretion of vWF in endotoxemic mice in the absence of the EPAC1 gene. Pharmacological inhibition of EPAC1 in vitro mimicked the EPAC1 -/- phenotype. EPAC1 regulated TNFalpha-triggered vWF secretion from human umbilical vein endothelial cells (HUVECs) in a phosphoinositide 3-kinases (PI3K)/endothelial nitric oxide synthase (eNOS)-dependent manner. Furthermore, EPAC1 activation reduced inflammation-triggered vWF release, both in vivo and in vitro . Our data delineate a novel regulatory role of EPAC1 in vWF secretion and shed light on potential development of new strategies to controlling thrombosis during inflammation. KEY POINT: PI3K/eNOS pathway-mediated, inflammation-triggered vWF secretion is the target of the pharmacological manipulation of the cAMP-EPAC system.

15.
Embase;
Preprint in English | EMBASE | ID: ppcovidwho-326764

ABSTRACT

The SARS-CoV-2 B.1.1.529 variant (Omicron) contains 15 mutations on the receptor-binding domain (RBD). How Omicron would evade RBD neutralizing antibodies (NAbs) requires immediate investigation. Here, we used high-throughput yeast display screening1,2 to determine the RBD escaping mutation profiles for 247 human anti-RBD NAbs and showed that the NAbs could be unsupervised clustered into six epitope groups (A-F), which is highly concordant with knowledge-based structural classifications3-5. Strikingly, various single mutations of Omicron could impair NAbs of different epitope groups. Specifically, NAbs in Group A-D, whose epitope overlap with ACE2-binding motif, are largely escaped by K417N, G446S, E484A, and Q493R. Group E (S309 site)6 and F (CR3022 site)7 NAbs, which often exhibit broad sarbecovirus neutralizing activity, are less affected by Omicron, but still, a subset of NAbs are escaped by G339D, N440K, and S371L. Furthermore, Omicron pseudovirus neutralization showed that single mutation tolerating NAbs could also be escaped due to multiple synergetic mutations on their epitopes. In total, over 85% of the tested NAbs are escaped by Omicron. Regarding NAb drugs, the neutralization potency of LYCoV016/LY-CoV555, REGN10933/REGN10987, AZD1061/AZD8895, and BRII-196 were greatly reduced by Omicron, while VIR-7831 and DXP-604 still function at reduced efficacy. Together, data suggest Omicron would cause significant humoral immune evasion, while NAbs targeting the sarbecovirus conserved region remain most effective. Our results offer instructions for developing NAb drugs and vaccines against Omicron and future variants.

16.
Information Communication & Society ; : 18, 2021.
Article in English | Web of Science | ID: covidwho-1585603

ABSTRACT

In efforts to curb the spread of COVID-19, many countries have implemented a variety of lockdown and quarantine measures. With substantially reduced face-to-face interactions, many people may have relied heavily on social media for connection, information, and entertainment. However, little is known about the psychological and physical health implications of social media use during strict lockdown. The current study investigates the associations of social media use with psychological well-being and physical health among Wuhan residents (N = 1214). Our findings showed that non-COVID related self-disclosure was positively associated with psychological well-being, while COVID related information consumption and sharing were negatively associated with psychological well-being. Further, more generic use of social media was associated with lower psychological well-being, which in turn related to more somatic symptoms. Quarantined people used social media more frequently than non-quarantined people. Importantly, the negative association between social media use and psychological well-being was significantly stronger for quarantined people than unquarantined people.

17.
22nd Annual Conference of the International Speech Communication Association, INTERSPEECH 2021 ; 5:3641-3645, 2021.
Article in English | Scopus | ID: covidwho-1529068

ABSTRACT

Fast and affordable solutions for COVID-19 testing are necessary to contain the spread of the global pandemic and help relieve the burden on medical facilities. Currently, limited testing locations and expensive equipment pose difficulties for individuals seeking testing, especially in low-resource settings. Researchers have successfully presented models for detecting COVID-19 infection status using audio samples recorded in clinical settings, suggesting that audio-based Artificial Intelligence models can be used to identify COVID-19. Such models have the potential to be deployed on smartphones for fast, widespread, and low-resource testing. However, while previous studies have trained models on cleaned audio samples collected mainly from clinical settings, audio samples collected from average smartphones may yield suboptimal quality data that is different from the clean data that models were trained on. This discrepancy may add a bias that affects COVID-19 status predictions. To tackle this issue, we propose a multi-branch deep learning network that is trained and tested on crowdsourced data where most of the data has not been manually processed and cleaned. Furthermore, the model achieves state-of-art results for the COUGHVID dataset. After breaking down results for each category, we have shown an AUC of 0.99 for audio samples with COVID-19 positive labels. © 2021 ISCA

18.
International Journal of Radiation Oncology, Biology, Physics ; 111(3):e89-e89, 2021.
Article in English | Academic Search Complete | ID: covidwho-1428044

ABSTRACT

Healthcare data often exist in silos and in unstructured formats that limit interoperability and require tedious manual extraction. Our institution has adopted a flexible and scalable big data platform built on Hadoop that integrates data from Epic/Clarity as well as Aria and allows users to leverage modern data science tools to facilitate access. We hypothesize that a data analytics and visualization dashboard can be built using open-source tools that will (1) allow non-technical users to explore de-identified clinical data within our institutional big data platform and (2) connect with repositories of molecular data to demonstrate potential methods of integrating clinical and basic science data. De-identified patient-level radiation oncology data from the institutional big data platform (Hadoop) were extracted with the python packages pyodbc and pandas. For the purposes of this dashboard, radiation oncology specific clinical data elements were queried including the date of first radiation treatment, treatment location, treatment modality (SBRT, external beam, SRS, TBI, LDR/HDR brachytherapy), ICD10 codes, anatomic treatment site, number of fractions, treatment prescription, and dose per fraction. A python client connection with the publicly accessible instance of cBioPortal for Cancer Genomics was established using the Bravado library. Data transformation and cleaning was performed in python using panda's data frames. A web-based dashboard to facilitate user-defined visualizations was implemented using the Dash python library and interactive visualizations of subsets of extracted data were generated in real-time using the plotly plotting library. We developed a web-based dashboard that gives users without extensive programming expertise the ability to explore de-identified clinical data extracted from Hadoop. As proof of principle, the dashboard was used to visualize the clinical impact of the COVID-19 pandemic on radiation oncology patient volumes, revealing a significant decline in new radiation treatments in April and May of 2020 (-54% and -36% compared to 2019) during the initial COVID-19 surge. Furthermore, the dashboard allows users to interact with the cBioPortal for Cancer Genomics repository, which currently houses clinical and molecular data from 301 publicly available studies spanning 869 different cancer types. This interface with cBioPortal illustrates the potential for future integration of clinically meaningful sequencing results with clinical outcomes data. We built an interactive web-based dashboard to enable general users' easy access to de-identified clinical data stored within the institutional big data platform. Additional data sources, including external molecular data can be connected to the dashboard allowing for future integration. [ABSTRACT FROM AUTHOR] Copyright of International Journal of Radiation Oncology, Biology, Physics is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

19.
2nd International Conference on Artificial Intelligence and Information Systems, ICAIIS 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1394250

ABSTRACT

During the 2019-nCoV epidemic, in order to effectively prevent the spread of the virus, people generally wore masks when entering public places, rendering traditional facial recognition technology ineffective. This paper constructs a dataset of face images with masks, and proposes a face recognition algorithm for masks based on deep learning. Applying the TensorFlow framework and proposing an improved MTCNN algorithm to cluster the effective feature regions of the face;using the FaceNet model shortens the time of face detection and improves the efficiency of face recognition. The test results show that the improved model has an average accuracy of 91% in recognition of faces wearing masks, and an average recall rate of 92%. Compared with the unimproved algorithm, the candidate frame of the improved algorithm focuses on important feature information to make it accurate. The rate increased by an average of 3%. © 2021 ACM.

20.
25th International Conference on Pattern Recognition (ICPR) ; : 9333-9339, 2021.
Article in English | Web of Science | ID: covidwho-1388102

ABSTRACT

A number of methods based on deep learning have been applied to medical image segmentation and have achieved state-of-the-art performance. Due to the importance of chest x-ray data in studying COVID-19, there is a demand for state-of-the-art models capable of precisely segmenting soft tissue on the chest x-rays. The dataset for exploring best segmentation model is from Montgomery and Shenzhen hospital which had opened in 2014. The most famous technique is U-Net which has been used to many medical datasets including the Chest X-rays. However, most variant U-Nets mainly focus on extraction of contextual information and skip connections. There is still a large space for improving extraction of spatial features. In this paper, we propose a dual encoder fusion U-Net framework for Chest X-rays based on Inception Convolutional Neural Network with dilation, Densely Connected Recurrent Convolutional Neural Network, which is named DEFU-Net. The densely connected recurrent path extends the network deeper for facilitating contextual feature extraction. In order to increase the width of network and enrich representation of features, the inception blocks with dilation are adopted. The inception blocks can capture globally and locally spatial information from various receptive fields. At the same time, the two paths are fused by summing features, thus preserving the contextual and spatial information for decoding part. This multi-learning-scale model is benefiting in Chest X-ray dataset from two different manufacturers (Montgomery and Shenzhen hospital). The DEFU-Net achieves the better performance than basic U-Net, residual U-Net, BCDU-Net, R2U-Net and attention R2U-Net. This model has proved the feasibility for mixed dataset and approaches state-of-the-art. The source code for this proposed framework is public https://github.com/uceclz0/DEFU-Net.

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