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1.
American Journal of Respiratory and Critical Care Medicine ; 205:1, 2022.
Article in English | English Web of Science | ID: covidwho-1880254
2.
Journal of University of Science and Technology of China ; 50(8):1124-1133, 2020.
Article in Chinese | Scopus | ID: covidwho-1875879

ABSTRACT

The traditional SEIR (susceptible-exposed-infectious-recovered/removed) model is a simplified dynamical predictive model which does not consider the impact of changes in the anti-epidemic policy. We take the US anti-epidemic policy and the incubation period characteristic of COVID-19 into account to propose the TRP-SEAMRD(test-restricted-phased SEAMRD) model for the pandemic in US. The model fits well with the figures of COVID-19 infections, recovery and death in the United States during February ~ August 2020. According to the data generated from the model, some of the characteristics of COVID- 19 can be ed. Based on the TRP-SEAMRD model, we can analyze the impact of the improper anti¬epidemic policy at the early stage of the epidemic. The effect of the subsequent “stay at home”epidemic controlling measures is also considered and analyzed. Finally, future development of the pandemic in the US under different degrees of social control is simulated,offering a reference for formulating scientific anti¬epidemic measures. © 2020, Editorial Department of Journal of University of Science and Technology of China. All rights reserved.

3.
Adverse Drug Reactions Journal ; 24(4):169-174, 2022.
Article in Chinese | Scopus | ID: covidwho-1875842

ABSTRACT

Objective To explore the occurrence and influencing factors of serum uric acid elevation in patients with coronavirus disease 2019 (COVID⁃19) treated with favipiravir. Methods Medical records of patients with COVID⁃19 who were hospitalized in Beijing Ditan Hospital between June 1, 2020 and June 30, 2021 and treated with the 5- or 10-day regimen of favipiravir were collected and retrospectively analyzed. After favipiravir withdrawal, if the elevation in serum uric acid was ≥30% of baseline level, it was defined as serum uric acid elevation. Then patients were divided into serum uric acid elevation group and non-serum uric acid elevation group. The clinical characteristics such as gender, age, body mass index, comorbidities, smoking and drinking behavior, COVID⁃19 grade, favipiravir regimen, and serum uric acid level and renal function before treatment in patients between the 2 groups were compared. Influencing factors of favipiravir⁃associated serum uric acid elevation was analyzed using multivariate logistic regression method. Results A total of 179 patients were included in the analysis, including 104 (58.1%) males and 75 (41.9%) females, aged from 19 to 70 years with a median age of 43 years. The level of serum uric acid in 179 patients after favipiravir treatment was significantly higher than before [(451±119) μmol/L vs. (332±94) μmol/L, P<0.001]. The change rate of serum uric acid from baseline level ranged from -57.1% to 157.8% with the median of 38.6%. The elevation in serum uric acid of ≥ 30% of baseline level occurred in 108 (60.3%) patients. The incidences of serum uric acid elevation in patients treated with 5-day and 10-day regi⁃ mens of favipiravir were 46.8% (36/77) and 70.6% (72/102), respectively, and the difference between them was significant (P=0.001). Multivariate logistic regression analysis showed that body mass index 24.0 to <28.0 kg/m2 (OR=3.109, 95%CI: 1.209-7.994, P=0.019) and 10-day regimen of favipiravir (OR=3.017, 95%CI: 1.526-5.964, P=0.001) were independent risk factors for favipiravir⁃associated serum uric acid elevation. Conclusions More than half of COVID⁃19 patients treated with favipiravir can develop serum uric acid elevation. Overweight and 10-day regimen of favipiravir are independent risk factors for serum uric acid elevation in patients. © 2022 Adverse Drug Reactions Journal.

4.
Frontiers in Political Science ; 4, 2022.
Article in English | Scopus | ID: covidwho-1875427

ABSTRACT

Open science provides a bright light for global engineering and technology cooperation and promoting global sustainable development. The International Knowledge Centre for Engineering Sciences and Technology (IKCEST), a category II center under the auspices of UNESCO based in Beijing, aims at providing knowledge-based services at a global scale for policy-makers and engineering science and technology professionals in the world, with particular reference to the developing countries. IKCEST has established a platform with data resources and knowledge services at the core, which includes one general platform and several sub-platforms in its prioritized areas such as the disaster risk reduction (DRR), the intelligent city (ICITY), the engineering education (ENGEDU) and the silk road sciences and technology (SRST). Since the platform was put into operation, it has launched 38 knowledge applications (APPs), serving 3.26 million users from 220 countries and regions worldwide, and offered training for more than 18,000 persons from developing countries. In face of the pandemic, IKCEST set up a COVID-19 column which received positive feedback from users across the globe, the introductory video of which was publicized on the UNESCO official website. As a knowledge hub supporting global sustainable development goals (SDGs) and an open platform for global engineering initiatives, IKCEST will spare no efforts to make greater contributions to providing more tailored and valuable knowledge-based services for global users. Copyright © 2022 Chen, Liu, Ma, Zhang and Fang.

5.
Journal of Neuropathology and Experimental Neurology ; 81(6):475-475, 2022.
Article in English | Web of Science | ID: covidwho-1865873
6.
Chinese Journal of Experimental Traditional Medical Formulae ; 28(1):150-156, 2022.
Article in Chinese | Scopus | ID: covidwho-1847755

ABSTRACT

[] Objective: To retrospectively analyze the clinical data of 52 patients with coronavirus disease-2019 (COVID-19) and explore the clinical efficacy of modified Sanxiaoyin on mild/moderate COVID-19 patients. Method: The propensity score matching method was used to collect the clinical data of mild or moderate COVID-19 patients enrolled in the designated hospital of the Second Hospital of Jingzhou from December 2019 to May 2020. A total of 26 eligible patients who were treated with modified Sanxiaoyin were included in the observation group,and the 26 patients treated with conventional method were the regarded as the control. The disappearance of clinical symptoms,disappearance time of main symptoms,efficacy on traditional Chinese medicine(TCM)symptoms,hospitalization duration,laboratory test indicators,and CT imaging changes in the two groups were compared. Result: The general data in the two groups were insignificantly different and thus they were comparable. After 7 days of treatment,the disappearance rate of fever,cough, fatigue,dry throat,anorexia,poor mental state,and poor sleep quality in the observation group was higher than that in the control group(P<0.05),and the difference in the disappearance rate of expectoration and chest distress was insignificant. For the cases with the disappearance of symptoms,the main symptoms(fever, cough,fatigue,dry throat,anorexia,chest distress)disappeared earlier in the observation group than in the control group(P<0.01). After 7 days of treatment,the scores of the TCM symptom scale of both groups decreased(P<0.01),and the decrease of the observation group was larger that of the control group(P<0.01). All patients in the two groups were cured and discharged. The average hospitalization duration in the observation group[(12.79±2.68)d]was shorter than that in the control group[(15.27±3.11)d](P<0.01). The effective rate in the observation group(92.31%,24/26)was higher than that in the control group(76.92%,20/26). After 7 days of treatment,the lymphocyte(LYM)count increased(P<0.05),and white blood cell(WBC)count and neutrophil(NEUT)count decreased insignificantly in the two groups. Moreover,levels of C-reactive protein (CRP),erythrocyte sedimentation rate(ESR),and procalcitonin(PCT)reduced in the two groups after treatment(P<0.01)and the reduction in the observation group was larger than that in the control group (P<0.01). Through 7 days of treatment,the total effective rate on pulmonary shadow in the observation group (90.00%,18/20)was higher than that in the control group(77.27%,17/22)(P>0.05)and the improvement of lung shadow in the observation group was better than that in the control group(P<0.01). Conclusion:Modified Sanxiaoyin can significantly alleviate fever,cough,fatigue,anorexia,chest distress,poor sleep quality,and other symptoms of patients with mild or moderate COVID-19,improve biochemical indicators,and promote the recovery of lung function. This paper provides clinical evidence for the application of modified Sanxiaoyin in the treatment of mild or moderate COVID-19. © 2022, China Academy of Chinese Medical Sciences Institute of Chinese Materia Medica. All rights reserved.

7.
PubMed; 2020.
Preprint in English | PubMed | ID: ppcovidwho-335867

ABSTRACT

COVID-19 is one of the most consequential pandemics in the last century, yet the biological mechanisms that confer disease risk are incompletely understood. Further, heterogeneity in disease outcomes is influenced by race, though the relative contributions of structural/social and genetic factors remain unclear. Very recent unpublished work has identified two genetic risk loci that confer greater risk for respiratory failure in COVID-19: the ABO locus and the 3p21.31 locus. To understand how these loci might confer risk and whether this differs by race, we utilized proteomic profiling and genetic information from three cohorts including black and white participants to identify proteins influenced by these loci. We observed that variants in the ABO locus are associated with levels of CD209/DC-SIGN, a known binding protein for SARS-CoV and other viruses, as well as multiple inflammatory and thrombotic proteins, while the 3p21.31 locus is associated with levels of CXCL16, a known inflammatory chemokine. Thus, integration of genetic information and proteomic profiling in biracial cohorts highlights putative mechanisms for genetic risk in COVID-19 disease.

8.
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
9.
Physical Review Physics Education Research ; 18(1), 2022.
Article in English | Scopus | ID: covidwho-1831596

ABSTRACT

This paper examines the prevalence of rapid answer copying among university students completing online homework for an introductory level calculus-based physics course taught remotely during the COVID pandemic. We first compared the attempt duration distribution of 26 problems, between 42 students who self-reported as having completed the homework by themselves against the rest of the class. Significant differences were detected for 3 out of 26 problems. We then identified abnormally short problem attempts indicative of potential rapid answer copying, by fitting the attempt duration distribution of each problem with finite-mixture models, using mixtures of either normal or skewed distributions. We detected a significantly smaller fraction of short attempts from self-reporting students on only 3 out of 26 problems and found no statistically significant difference in percentage correct of short attempts between the populations. In conclusion, our analysis did not find evidence indicating widespread rapid answer copying among students. We also explored differences in learning behavior between the two populations by applying process mining to the event logs of one of the homework learning modules, which reveals that some students may have copied answers after spending a longer time or using multiple attempts on a given problem. However, this form of answer copying is also unlikely to be prevalent since the percentage correct on normal attempts is also similar between the two populations on most problems. © 2022 authors. Published by the American Physical Society.

10.
Production and Operations Management ; : 18, 2022.
Article in English | Web of Science | ID: covidwho-1822058

ABSTRACT

COVID-19 is a highly contagious disease that has spread to most countries at unprecedented transmission speed. Medical resources and treatments provided by the healthcare system help reduce the mortality rate and spread of COVID-19 by isolating infectious individuals. We introduce a modified SEIR model that considers individuals access to limited medical resources to characterize the central role of medical resources during the pandemic. We discuss how the three hospital admission policies (hierarchy, mixed, and Fangcang healthcare system) affect the spread of the disease and the number of deaths and infections. We find that the Fangcang system results in the least number of infections, deaths, and occupied beds. When hospital capacity is relatively high or the transmission rate of the mildly infected patient is not ignorable, a mixed system can lead to fewer infections and deaths than a hierarchy system, but greater numbers of occupied beds. This occurs by preventing disease transmission to a great extent. The results are confirmed by our surveys with healthcare workers in major hospitals in Wuhan, China. We also investigate the performance of the three healthcare systems under a social distancing policy. We find that the Fangcang system results in the largest reduction in infections and deaths, especially even when the medical capacity is small. Moreover, we compare a one-time off policy with a bed trigger policy. We find that a one-time off policy could achieve the similar performance as bed trigger policy when it is initiated neither too early nor too late.

11.
PubMed; 2021.
Preprint in English | PubMed | ID: ppcovidwho-333852

ABSTRACT

The newly emerging variants of SARS-CoV-2 from India (Delta variant) and South America (Lambda variant) have led to a higher infection rate of either vaccinated or unvaccinated people. We found that sera from Pfizer-BioNTech vaccine remain high reactivity toward the receptor binding domain (RBD) of Delta variant while it drops dramatically toward that of Lambda variant. Interestingly, the overall titer of antibodies of Pfizer-BioNTech vaccinated individuals drops 3-fold after 6 months, which could be one of major reasons for breakthrough infections, emphasizing the importance of potential third boost shot. While a therapeutic antibody, Bamlanivimab, decreases binding affinity to Delta variant by ~20 fold, it fully lost binding to Lambda variant. Structural modeling of complexes of RBD with human receptor, Angiotensin Converting Enzyme 2 (ACE2), and Bamlanivimab suggest the potential basis of the change of binding. The data suggest possible danger and a potential surge of Lambda variant in near future.

12.
PubMed; 2021.
Preprint in English | PubMed | ID: ppcovidwho-333792

ABSTRACT

Patients with COVID-19 present with a wide variety of clinical manifestations. Thromboembolic events constitute a significant cause of morbidity and mortality in patients infected with SARS-CoV-2. Severe COVID-19 has been associated with hyperinflammation and pre-existing cardiovascular disease. Platelets are important mediators and sensors of inflammation and are directly affected by cardiovascular stressors. In this report, we found that platelets from severely ill, hospitalized COVID-19 patients exhibit higher basal levels of activation measured by P-selectin surface expression, and have a poor functional reserve upon in vitro stimulation. Correlating clinical features to the ability of plasma from COVID-19 patients to stimulate control platelets identified ferritin as a pivotal clinical marker associated with platelet hyperactivation. The COVID-19 plasma-mediated effect on control platelets was highest for patients that subsequently developed inpatient thrombotic events. Proteomic analysis of plasma from COVID-19 patients identified key mediators of inflammation and cardiovascular disease that positively correlated with in vitro platelet activation. Mechanistically, blocking the signaling of the FcgammaRIIa-Syk and C5a-C5aR pathways on platelets, using antibody-mediated neutralization, IgG depletion or the Syk inhibitor fostamatinib, reversed this hyperactivity driven by COVID-19 plasma and prevented platelet aggregation in endothelial microfluidic chamber conditions, thus identifying these potentially actionable pathways as central for platelet activation and/or vascular complications in COVID-19 patients. In conclusion, we reveal a key role of platelet-mediated immunothrombosis in COVID-19 and identify distinct, clinically relevant, targetable signaling pathways that mediate this effect. These studies have implications for the role of platelet hyperactivation in complications associated with SARS-CoV-2 infection. Cover illustration: ONE-SENTENCE SUMMARY: The FcgammaRIIA and C5a-C5aR pathways mediate platelet hyperactivation in COVID-19.

13.
PubMed; 2021.
Preprint in English | PubMed | ID: ppcovidwho-333717

ABSTRACT

PURPOSE: To examine characteristics of coronavirus disease 2019 (COVID-19) decedents in California (CA) and evaluate for disproportionate mortality across race/ethnicity and ethnicity/nativity. METHODS: COVID-19 deaths were identified from death certificates. Age-adjusted mortality rate ratios (MRR) were compared across race/ethnicity. Proportionate mortality rates (PMR) were compared across race/ethnicity and by ethnicity/nativity. RESULTS: We identified 10,200 COVID-19 deaths in CA occurring February 1 through July 31, 2020. Decedents tended to be older, male, Hispanic, foreign-born, and have lower educational attainment. MRR indicated elevated COVID-19 morality rates among Asian/Pacific Islander, Black, and Hispanic groups compared with the White group, with Black and Hispanic groups having the highest MRR at 2.75 (95%CI:2.54-2.97) and 4.18 (95%CI: 3.99-4.37), respectively. Disparities were larger at younger ages. Similar results were observed with PMR, which remained in analyses stratified by education. Elevated PMR were observed in all ethnicity/nativity groups, especially foreign-born Hispanic individuals, relative to U.S.-born non-Hispanic individuals, were generally larger at younger ages, and persisted after stratifying by education. CONCLUSIONS: Differential COVID-19 mortality was observed in California across racial/ethnic groups and by ethnicity/nativity groups with evidence of greater disparities among younger age groups. Identifying COVID-19 disparities is an initial step towards mitigating disease impacts in vulnerable communities.

14.
PubMed; 2020.
Preprint in English | PubMed | ID: ppcovidwho-333498

ABSTRACT

OBJECTIVE: The outbreak of novel coronavirus disease 2019 (COVID-19) imposed a substanal health burden in mainland China and remains a global epidemic threat. Our objectives are to assess the case fatality risk (CFR) among CO VID-19 patients detected in mainland China, stratified by clinical category and age group. METHODS: We collected individual information on laboratory-confirmed COVID-19 cases from publicly available official sources from December 29, 2019 to February 23, 2020. We explored the risk factors associated with mortality. We used methods accounting for right-censoring and survival analyses to estimatethe CFR among detected cases. RESULTS: Of 12,863 cases reported outside Hubei, we obtained individual records for 9,651 cases, including 62 deaths and 1,449 discharged cases. The deceased were significantly older than discharged cases (median age: 77 vs 39 years, p<0.001). 58% (36/62) were male. Older age (OR 1.18 per year;95% CI: 1.14 to 1.22), being male (OR 2.02;95% CI: 1.02 to 4.03), and being treated in less developed economic regions (e.g., West and Northeast vs. East, OR 3.93;95 %Cl:1.74 to 8.85) were mortality risk factors. The estimated CFR was 0.89-1.24% among all cases. The fatality risk among critical patients was 2-fold higher than that among severe and critical patients, and 24-fold higher than that among moderate, severe and critical patients. CONCLUSIONS: Our estimates of CFR based on laboratory-confirmed cases ascertained outside of Hubei suggest that COVID-19 is not as severe as severe acute respiratory syndrome and Middle East respiratory syndrome, but more similar to the mortality risk of 2009 H1N1 influenza pandemic in hospitalized patients. The fatality risk of COVID-19 is higher in males and increases with age. Our study improves the severity assessment of the ongoing epidemic and can inform the COVID-19 outbreak response in China and beyond.

15.
14th IEEE International Conference on Computer Research and Development, ICCRD 2022 ; : 161-166, 2022.
Article in English | Scopus | ID: covidwho-1794839

ABSTRACT

Since the end of 2019, a new type of coronavirus pneumonia (COVID-19) has broken out in Wuhan, and various topics about the development of the epidemic have spread in full swing on the Sina Weibo. In this paper, the web crawler is used to capture the relevant Weibo and popularity of the hot searches during the COVID-19 outbreak, and the Weibo related to the epidemic are extracted by the Bayesian text classification method. Then, the potential Dirichlet model (LDA) was established to obtain the public opinion topic model, and ten public opinion topics were obtained to analyze the public opinion changes with the development of the epidemic. According to the topic model and the influence of daily time point on the popularity of Weibo, a multiple linear regression model is established to predict the popularity. Real-time analysis of changes in public opinion concerns provides reference for decision-making on epidemic prevention and control and information release. © 2022 IEEE.

16.
Surgical Technology International ; 39, 2021.
Article in English | Scopus | ID: covidwho-1789997

ABSTRACT

Telehealth has recently been used more often in an attempt to protect practitioners and patients during the 2019 coronavirus infectious disease (COVID-19) crisis. Despite telehealth’s existence, there was no prior need to fully realize its potential. Recently, technological innovations in orthopaedic surgery have assisted in making this modality more useful. However, it is important to continually educate the medical community regarding these technologies and their interplay to improve patient care. Therefore, our purpose is to pro-vide information on telehealth by assessing: (1) steps the hospital/system are taking to reduce COVID-19 exposure for teams and patients;(2) new technologies allowing for the optimization of patient safety;and (3) use of telehealth for postoperative follow up. We will demonstrate that telehealth and its associated strategies can be used effectively to decrease COVID-19 exposure risks for both medical staff and patients during these rapidly changing and uncertain times. © 2021 Surgical Technology International™.

17.
Journal of Image and Graphics ; 27(3):655-671, 2022.
Article in Chinese | Scopus | ID: covidwho-1789679

ABSTRACT

The development of medical imaging, artificial intelligence (AI) and clinical applications derived from AI-based medical imaging has been recognized in past two decades. The improvement and optimization of AI-based technologies have been significantly applied to various of clinical scenarios to strengthen the capability and accuracy of diagnosis and treatment. Nowadays, China has been playing a major role and making increasing contributions in the field of AI-based medical imaging. More worldwide researchers in the context of AI-based medical imaging have contributed to universities and institutions in China. The number of research papers published by Chinese scholars in top international journals and conferences like AI-based medical imaging has dramatically increased annually. Some AI-based medical imaging international conferences and summits have been successfully held in China. There is an increasing number of traditional medical, internet technology and AI enterprises contributing to the research and development of AI-based medical imaging products. More collaborative medical research projects have been implemented for AI-based medical imaging. The Chinese administrations have also planned relevant policies and issued strategic plans for AI-based medical imaging, and included the intelligent medical care as one of the key tasks for the development of new generation of AI in China in 2030. In order to review China's contribution for AI-based medical imaging, we conducted a 20 years review for AI-based medical imaging forecasting in China. Specifically, we summarized all papers published by Chinese scholars in the top AI-based medical imaging journals and conferences including Medical Image Analysis (MedIA), IEEE Transactions on Medical Imaging (TMI), and Medical Image Computing and Computer Assisted Intervention (MICCAI) in the past 20 years. The detailed quantitative metrics like the number of published papers, authorship, affiliations, author's cooperation network, keywords, and the number of citations were critically reviewed. Meanwhile, we briefly summarized some milestone events of AI-based medical imaging in China, including the renowned international and domestic conferences in AI-based medical imaging held in China, the release of the "The White Paper on Medical Imaging Artificial Intelligence in China", as well as China's contributions during the COVID-19(corona virus desease 2019) pandemic. For instance, the total number of published papers in the past 20 years and the proportion of published papers in 2021 by Chinese affiliations have reached to 333 and 37.29% in MedIA, 601 and 42.26% in TMI, and 985 and 44.26% in MICCAI. In those published papers by Chinese institutes, the proportion of the first and the corresponding Chinese authors is 71.97% in MedIA, 69.64% in TMI, and 77.4% in MICCAI in 2021. The average number of citations per paper by Chinese institutes is 22, 28, and 9 in MedIA, TMI, and MICCAI, respectively. In all published papers by Chinese institutes, the predominant research methods were transformed from conventional approaches to sparse representation in 2012, and to deep learning in 2017, which were close to the latest developmental trend of AI technologies. Besides conventional applications such as medical image registration, segmentation, reconstruction and computer-aided diagnosis, etc., the published papers also focused on healthcare quick response in terms of COVID-19 pandemic. The China-derived data and source codes have been sharing in the global context to facilitate worldwide AI-based medical imaging research and education. Our analysis could provide a reference for international scientific research and education for newly Chinese scholars and students based on the growth of the global AI-based medical imaging. Finally, we promoted technology forecasting on AI-based medical imaging as mentioned below. First, strengthen the capability of deep learning for AI-based medical imaging further, including optimal and efficient deep learning, generalizable deep learning, explainable d ep learning, fair deep learning, and responsible and trustworthy deep learning. Next, improve the availability and sharing of high-quality and benchmarked medical imaging datasets in the context of AI-based medical imaging development, validation, and dissemination are harnessed to reveal the key challenges in both basic scientific research and clinical applications. Third, focus on the multi-center and multi-modal medical imaging data acquisition and fusion, as well as integration with natural language such as diagnosis report. Fourth, awake doctors' intervention further to realize the clinical applications of AI-based medical imaging. Finally, conduct talent training, international collaboration, as well as sharing of open source data and codes for worldwide development of AI-based medical imaging. © 2022, Editorial Office of Journal of Image and Graphics. All right reserved.

18.
Review of Development Economics ; 2022.
Article in English | Scopus | ID: covidwho-1784736

ABSTRACT

In recent years, the relationship between agricultural commodities and crude oil has become increasingly close with the promotion of biofuel policies. This study examines the dynamic correlation between global crude oil futures and seven agricultural commodity futures by applying the consistent dynamic conditional correlation and dynamic equicorrelation models. The empirical results show that the dynamic correlation between the global crude oil futures market and China's agricultural futures market is weak compared to the global agricultural futures market. In particular, soybean oil has the strongest correlation with crude oil, while Dalian Commodity Exchange (DCE) corn and Zhengzhou Commodity Exchange wheat have the weakest correlation with crude oil. There is an indirect linkage between crude oil futures and DCE soybean meal and DCE soybean oil. Moreover, the dynamic correlation between crude oil and agricultural commodities increased during the financial crisis, the novel coronavirus (COVID-19) epidemic, and the crude oil crash crisis. Brent crude oil has a stronger co-movement with China's agricultural commodities than West Texas Intermediate crude oil and can better hedge the risk of agricultural commodities. The findings of this study provide some insights into the contagion risk management of crude oil futures and agricultural futures markets. © 2022 John Wiley & Sons Ltd.

19.
2022 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, WACVW 2022 ; : 202-209, 2022.
Article in English | Scopus | ID: covidwho-1769669

ABSTRACT

As the COVID-19 pandemic rampages across the world, the demands of video conferencing surge. To this end, real-time portrait segmentation becomes a popular feature to replace backgrounds of conferencing participants. While feature-rich datasets, models and algorithms have been offered for segmentation that extract body postures from life scenes, portrait segmentation has yet not been well covered in a video conferencing context. To facilitate the progress in this field, we introduce an open-source solution named PP-HumanSeg. This work is the first to construct a large-scale video portrait dataset that contains 291 videos from 23 conference scenes with 14K fine-labeled frames and extensions to multi-camera teleconferencing. Furthermore, we propose a novel Self-supervised Connectivity-aware Learning (SCL) for semantic segmentation, which introduces a self-supervised connectivity-aware loss to improve the quality of segmentation results from the perspective of connectivity. And we propose an ultra-lightweight model with SCL for practical portrait segmentation, which achieves the best trade-off between IoU and the speed of inference. Extensive evaluations on our dataset demonstrate the superiority of SCL and our model. The source code is available at https://github.com/PaddlePaddle/PaddleSeg. © 2022 IEEE.

20.
Discovery Medicine ; 31(164):121-127, 2021.
Article in English | Web of Science | ID: covidwho-1766877

ABSTRACT

Background. Few studies reported the risk factors of fatal outcome of hospitalized patients with coronavirus disease 2019 (COVID-19). We aimed to identify the independent risk factors associated with fatal outcome of hospitalized COVID-19 patients. Methods. The clinical data of 109 consecutive COVID-19 patients including 40 (36.7%) common cases and 69 (63.3%) severe cases were included and analyzed. Results: Multivariate regression analysis indicated that platelets (PLT, OR, 0.988;95% CI, 0.978-0.998;P=0.017) and C-reactive protein (CRP) (OR, 1.047;95% CI, 1.026-1.068;P<0.001) levels were the independent risk factors of fatal outcome in COVID-19 patients. The optimal cut-off value of PLT counts for predicting fatal outcome was 161x109/L with the area under receiver operating characteristic curve (AUROC) of 0.824 (95% CI, 0.739-0.890). The optimal cut-off value of CRP for the prediction of fatal outcome was 46.2 mg/L with the AUROC of 0.954 (95% CI, 0.896-0.985). The CRP levels had higher predictive values for fatal outcome than PLT (P=0.016). The cumulative survival rate was significantly higher in patients with PLT>161x10(9)/L compared with patients with PLT <= 161x10(9)/L (89.4% vs. 12.5%, log-rank test chi(2)=72.17;P<0.001). Survival rate of COVID-19 patients was prominently higher in CRP <= 46.2 mg/L patients compared with patients with CRP>46.2 mg/L (95.9% vs. 22.9%, log-rank test chi(2)=77.85;P<0.001). Conclusions. PLT counts and CRP levels could predict fatal outcome of hospitalized COVID-19 patients with relatively high accuracy.

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