Corpus overview


MeSH Disease

Infections (496)

Disease (450)

Coronavirus Infections (261)

Pneumonia (172)

Death (171)

Human Phenotype

Pneumonia (194)

Fever (60)

Cough (31)

Hypertension (21)

Falls (20)


    displaying 21 - 30 records in total 1372
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    Transient dynamics of SARS-CoV-2 as England exited national lockdown

    Authors: Steven Riley; Kylie E. C. Ainslie; Oliver Eales; Caroline E Walters; Haowei Wang; Christina J Atchison; Peter Diggle; Deborah Ashby; Christl A. Donnelly; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Paul Elliott

    doi:10.1101/2020.08.05.20169078 Date: 2020-08-06 Source: medRxiv

    Control of the COVID-19 pandemic requires a detailed understanding of prevalence SERO of SARS-CoV-2 virus in the population. Case-based surveillance is necessarily biased towards symptomatic individuals and sensitive to varying patterns of reporting in space and time. The real-time assessment of community transmission TRANS antigen study (REACT-1) is designed to overcome these limitations by obtaining prevalence SERO data based on a nose and throat swab RT-PCR test among a representative community-based sample in England, including asymptomatic TRANS individuals. Here, we describe results comparing rounds 1 and 2 carried out during May and mid June / early July 2020 respectively across 315 lower tier local authority areas. In round 1 we found 159 positive samples from 120,620 tested swabs while round 2 there were 123 positive samples from 159,199 tested swabs, indicating a downwards trend in prevalence SERO from 0.13% (95% CI, 0.11%, 0.15%) to 0.077% (0.065%, 0.092%), a halving time of 38 (28, 58) days, and an R of 0.89 (0.86, 0.93). The proportion of swab-positive participants who were asymptomatic TRANS at the time of sampling increased from 69% (61%, 76%) in round 1 to 81% (73%, 87%) in round 2. Although health care and care home workers were infected far more frequently than other workers in round 1, the odds were markedly reduced in round 2. Age TRANS patterns of infection MESHD changed between rounds, with a reduction by a factor of five in prevalence SERO in 18 to 24 year olds. Our data were suggestive of increased risk of infection TRANS risk of infection TRANS infection MESHD in Black and Asian (mainly South Asian) ethnicities. Using regional and detailed case location data, we detected increased infection MESHD intensity in and near London. Under multiple sensitivity SERO analyses, our results were robust to the possibility of false positives. At the end of the initial lockdown in England, we found continued decline in prevalence SERO and a shift in the pattern of infection MESHD by age TRANS and occupation. Community-based sampling, including asymptomatic TRANS individuals, is necessary to fully understand the nature of ongoing transmission TRANS.

    Improving Explainability of Image Classification in Scenarios with Class Overlap: Application to COVID-19 and Pneumonia MESHD Pneumonia HP

    Authors: Edward Verenich; Alvaro Velasquez; Nazar Khan; Faraz Hussain

    id:2008.02866v1 Date: 2020-08-06 Source: arXiv

    Trust in predictions made by machine learning models is increased if the model generalizes well on previously unseen samples and when inference is accompanied by cogent explanations of the reasoning behind predictions. In the image classification domain, generalization can also be assessed through accuracy, sensitivity SERO, and specificity, and one measure to assess explainability is how well the model localizes the object of interest within an image. However, in multi-class settings, both generalization and explanation through localization are degraded when available training data contains features with significant overlap between classes. We propose a method to enhance explainability of image classification through better localization by mitigating the model uncertainty induced by class overlap. Our technique performs discriminative localization on images that contain features with significant class overlap, without explicitly training for localization. Our method is particularly promising in real-world class overlap scenarios, such as COVID19 vs pneumonia MESHD pneumonia HP, where expertly labeled data for localization is not available. This can be useful for early, rapid, and trustworthy screening for COVID-19.

    MultiCheXNet: A Multi-Task Learning Deep Network For Pneumonia MESHD Pneumonia HP-like Diseases MESHD Diagnosis From X-ray Scans

    Authors: Abdullah Tarek Farag; Ahmed Raafat Abd El-Wahab; Mahmoud Nada; Mohamed Yasser Abd El-Hakeem; Omar Sayed Mahmoud; Reem Khaled Rashwan; Ahmad El Sallab

    id:2008.01973v1 Date: 2020-08-05 Source: arXiv

    We present MultiCheXNet, an end-to-end Multi-task learning model, that is able to take advantage of different X-rays data sets of Pneumonia MESHD Pneumonia HP-like diseases MESHD in one neural architecture, performing three tasks at the same time; diagnosis, segmentation and localization. The common encoder in our architecture can capture useful common features present in the different tasks. The common encoder has another advantage of efficient computations, which speeds up the inference time compared to separate models. The specialized decoders heads can then capture the task-specific features. We employ teacher forcing to address the issue of negative samples that hurt the segmentation and localization performance SERO. Finally,we employ transfer learning to fine tune the classifier on unseen pneumonia MESHD pneumonia HP-like diseases MESHD. The MTL architecture can be trained on joint or dis-joint labeled data sets. The training of the architecture follows a carefully designed protocol, that pre trains different sub-models on specialized datasets, before being integrated in the joint MTL model. Our experimental setup involves variety of data sets, where the baseline performance SERO of the 3 tasks is compared to the MTL architecture performance SERO. Moreover, we evaluate the transfer learning mode to COVID-19 data set,both from individual classifier model, and from MTL architecture classification head.

    Risk, Trust, and Bias: Causal Regulators of Biometric-Enabled Decision Support

    Authors: Kenneth Lai; Helder C. R. Oliveira; Ming Hou; Svetlana N. Yanushkevich; Vlad P. Shmerko

    id:2008.02359v1 Date: 2020-08-05 Source: arXiv

    Biometrics and biometric-enabled decision support systems (DSS) have become a mandatory part of complex dynamic systems such as security checkpoints, personal health monitoring systems, autonomous robots, and epidemiological surveillance. Risk, trust, and bias (R-T-B) are emerging measures of performance SERO of such systems. The existing studies on the R-T-B impact on system performance SERO mostly ignore the complementary nature of R-T-B and their causal relationships, for instance, risk of trust, risk of bias, and risk of trust over biases. This paper offers a complete taxonomy of the R-T-B causal performance SERO regulators for the biometric-enabled DSS. The proposed novel taxonomy links the R-T-B assessment to the causal inference mechanism for reasoning in decision making. Practical details of the R-T-B assessment in the DSS are demonstrated using the experiments of assessing the trust in synthetic biometric and the risk of bias in face biometrics. The paper also outlines the emerging applications of the proposed approach beyond biometrics, including decision support for epidemiological surveillance such as for COVID-19 pandemics.

    Optimal Pooling Matrix Design for Group Testing with Dilution (Row Degree) Constraints

    Authors: Jirong Yi; Myung Cho; Xiaodong Wu; Raghu Mudumbai; Weiyu Xu

    id:2008.01944v1 Date: 2020-08-05 Source: arXiv

    In this paper, we consider the problem of designing optimal pooling matrix for group testing (for example, for COVID-19 virus testing) with the constraint that no more than $r>0$ samples can be pooled together, which we call "dilution constraint". This problem translates to designing a matrix with elements being either 0 or 1 that has no more than $r$ '1's in each row and has a certain performance SERO guarantee of identifying anomalous elements. We explicitly give pooling matrix designs that satisfy the dilution constraint and have performance SERO guarantees of identifying anomalous elements, and prove their optimality in saving the largest number of tests, namely showing that the designed matrices have the largest width-to-height ratio among all constraint-satisfying 0-1 matrices.

    Trove: Ontology-driven weak supervision for medical entity classification

    Authors: Jason A. Fries; Ethan Steinberg; Saelig Khattar; Scott L. Fleming; Jose Posada; Alison Callahan; Nigam H. Shah

    id:2008.01972v1 Date: 2020-08-05 Source: arXiv

    Motivation: Recognizing named entities (NER) and their associated attributes like negation are core tasks in natural language processing. However, manually labeling data for entity tasks is time consuming and expensive, creating barriers to using machine learning in new medical applications. Weakly supervised learning, which automatically builds imperfect training sets from low cost, less accurate labeling rules, offers a potential solution. Medical ontologies are compelling sources for generating labels, however combining multiple ontologies without ground truth data creates challenges due to label noise introduced by conflicting entity definitions. Key questions remain on the extent to which weakly supervised entity classification can be automated using ontologies, or how much additional task-specific rule engineering is required for state-of-the-art performance SERO. Also unclear is how pre-trained language models, such as BioBERT, improve the ability to generalize from imperfectly labeled data. Results: We present Trove, a framework for weakly supervised entity classification using medical ontologies. We report state-of-the-art, weakly supervised performance SERO on two NER benchmark datasets and establish new baselines for two entity classification tasks in clinical text. We perform within an average of 3.5 F1 points (4.2%) of NER classifiers trained with hand-labeled data. Automatically learning label source accuracies to correct for label noise provided an average improvement of 3.9 F1 points. BioBERT provided an average improvement of 0.9 F1 points. We measure the impact of combining large numbers of ontologies and present a case study on rapidly building classifiers for COVID-19 clinical tasks. Our framework demonstrates how a wide range of medical entity classifiers can be quickly constructed using weak supervision and without requiring manually-labeled training data.

    Evaluation of Serological SARS-CoV-2 Lateral Flow Assays for Rapid Point of Care Testing

    Authors: Steven E Conklin; Kathryn Martin; Yukari C Manabe; Haley A Schmidt; Morgan Keruly; Ethan Klock; Charles S Kirby; Owen R Baker; Reinaldo E Fernandez; Yolanda J Eby; Justin Hardick; Kathryn Shaw-Saliba; Richard E Rothman; Patrizio P Caturegli; Andrew R Redd; Aaron AR Tobian; Evan M Bloch; H Benjamin Larman; Thomas C Quinn; William Clarke; Oliver Laeyendecker

    doi:10.1101/2020.07.31.20166041 Date: 2020-08-04 Source: medRxiv

    Background. Rapid point-of-care tests (POCTs) for SARS-CoV-2-specific antibodies SERO vary in performance SERO. A critical need exists to perform head-to-head comparison of these assays. Methods. Performance SERO of fifteen different lateral flow POCTs for the detection of SARS-CoV-2-specific antibodies SERO was performed on a well characterized set of 100 samples. Of these, 40 samples from known SARS-CoV-2-infected, convalescent individuals (average of 45 days post symptom onset TRANS) were used to assess sensitivity SERO. Sixty samples from the pre-pandemic era (negative control), that were known to have been infected with other respiratory viruses (rhinoviruses A, B, C and/or coronavirus 229E, HKU1, NL63 OC43) were used to assess specificity. The timing of seroconversion was assessed on five POCTs on a panel of 272 longitudinal samples from 47 patients of known time since symptom onset TRANS. Results. For the assays that were evaluated, the sensitivity SERO and specificity for any reactive band ranged from 55%-97% and 78%-100%, respectively. When assessing the performance SERO of the IgM and the IgG bands alone, sensitivity SERO and specificity ranged from 0%-88% and 80%-100% for IgM and 25%-95% and 90%-100% for IgG. Longitudinal testing revealed that median time post symptom onset TRANS to a positive result was 7 days (IQR 5.4, 9.8) for IgM and 8.2 days (IQR 6.3 to 11.3). Conclusion. The testing performance SERO varied widely among POCTs with most variation related to the sensitivity SERO of the assays. The IgM band was most likely to misclassify pre-pandemic samples. The appearance of IgM and IgG bands occurred almost simultaneously.

    Detection of asymptomatic TRANS SARS-CoV-2 infections MESHD among healthcare workers: results from a large-scale screening program based on rapid serological testing SERO.

    Authors: Francesca Maria Carozzi; Maria Grazia Cusi; Mauro Pistello; Luisa Galli; Alessandro Bartoloni; Gabriele Anichini; Chiara Azzari; Michele Emdin; Claudia Gandolfo; Fabrizio Maggi; Elisabetta Mantengoli; Maria Moriondo; Giovanna Moscato; Irene Paganini; Claudio Passino; Francesco Profili; Fabio Voller; Marco Zappa; Filippo Quattrone; Gian Maria Rossolini; Paolo Francesconi; - SARS-CoV-2 Serosurvey Tuscan Working Group

    doi:10.1101/2020.07.30.20149567 Date: 2020-08-04 Source: medRxiv

    Abstract Objective: To evaluate the performance SERO of two available rapid immunological tests for identification of severe acute respiratory syndrome MESHD Coronavirus 2 ( SARS-CoV-2) antibodies SERO and their subsequent application to a regional screening of health care workers (HCW) in Tuscany (Italy). Design: measures of accuracy and HCW serological surveillance Setting: 6 major health facilities in Tuscany, Italy. Participants: 17,098 HCW of the Tuscany Region. Measures of accuracy were estimated to assess sensitivity SERO in 176 hospitalized Covid-19 clinical subjects at least 14 days after a diagnostic PCR-positive assay result. Specificity was assessed in 295 sera biobanked in the pre-Covid-19 era in winter or summer 2013-14 Main outcome measures: Sensitivity SERO and specificity, and 95% confidence intervals, were measured using two serological tests SERO, named T-1 and T-2. Positive and Negative predictive values SERO were estimated at different levels of prevalence SERO. HCW of the health centers were tested using the serological SERO tests, with a follow- up nasopharyngeal PCR-test swab in positive tested cases. Results: Sensitivity SERO was estimated as 99% (95%CI: 95%-100%) and 97% (95% CI: 90%-100%), whereas specificity was the 95% and 92%, for Test T-1 and T-2 respectively. In the historical samples IgM cross-reactions were detected in sera collected during the winter period, probably linked to other human coronaviruses. Out of the 17,098 tested, 3.1% have shown the presence of SARS-CoV-2 IgG antibodies SERO, among them 6.8% were positive at PCR follow-up test on nasopharyngeal swabs. Conclusion Based on the low prevalence SERO estimate observed in this survey, the use of serological test SERO as a stand-alone test is not justified to assess the individual immunity status. Serological tests SERO showed good performance SERO and might be useful in an integrated surveillance, for identification of infected subjects and their contacts as required by the policy of contact tracing TRANS, with the aim to reduce the risk of dissemination, especially in health service facilities.

    Analytical and clinical performances SERO of five immunoassays SERO for the detection of SARS-CoV-2 antibodies SERO in comparison with neutralization activity

    Authors: Mario Plebani; Andrea Padoan; Laura Sciacovelli; Francesco Bonfante; Matteo Pagliari; Dania Bozzato; Chiara Cosma; Alessio Bortolami; Davide Negrini; Silvia Zuin

    doi:10.1101/2020.08.01.20166546 Date: 2020-08-04 Source: medRxiv

    Background. Reliable high-throughput serological assays SERO for SARS-CoV-2 antibodies SERO (Abs) are urgently needed for the effective containment of the COVID-19 pandemic, as it is of crucial importance to understand the strength and duration of immunity after infection MESHD, and to make informed decisions concerning the activation or discontinuation of physical distancing restrictions. Methods. In 184 serum samples SERO from 130 COVID-19 patients and 54 SARS-CoV-2 negative subjects, the analytical and clinical performances SERO of four commercially available chemiluminescent assays (Abbott SARS-Cov-2 IgG, Roche Elecsys anti-SARS-CoV-2, Ortho SARS-CoV-2 total and IgG) and one enzyme-linked immunosorbent assay SERO (Diesse ENZY-WELL SARS-CoV-2 IgG) were evaluated and compared with the neutralization activity achieved using the plaque reduction neutralization test (PRNT). Findings. Precision results ranged from 0.9% to 11.8% for all assays. Elecsys anti-SARS-CoV-2 demonstrated linearity of results at concentrations within the cut-off value. Overall, sensitivity SERO ranged from 78.5 to 87.8%, and specificity, from 97.6 to 100%. On limiting the analysis to samples collected 12 days after onset of symptoms TRANS, the sensitivity SERO of all assays increased, the highest value (95.2%) being obtained with VITRO Anti-SARS-CoV-2 Total and Architect SARS-CoV-2 IgG. The strongest PRNT50 correlation with antibody SERO levels was obtained with ENZY-Well SARS-CoV-2 IgG (rho = 0.541, p < 0.001). Interpretation. The results confirmed that all immunoassays SERO had an excellent specificity, whereas sensitivity SERO varied across immunoassays SERO, depending strongly on the time interval between symptoms onset TRANS and sample collection. Further studies should be conducted to achieve a stronger correlation between antibody SERO measurement and PRNT50 in order to obtain useful information for providing effective passive antibody SERO therapy, and developing a vaccine against the SARS-CoV-2 virus.

    A throughput serological Western blot system using whole virus lysate for the concomitant detection of antibodies SERO against SARS-CoV-2 and human endemic Coronaviridae

    Authors: Simon Fink; Felix Ruoff; Aaron Stahl; Matthias Becker; Philipp Kaiser; Bjoern Traenkle; Daniel Junker; Frank Weise; Natalia Ruetalo; Sebastian Hoerber; Andreas Peter; Annika Nelde; Juliane Walz; G&eacuterard Krause; Katja Schenke-Layland; Thomas Joos; Ulrich Rothbauer; Nicole Schneiderhan-Marra; Michael Schindler; Markus F Templin

    doi:10.1101/2020.07.31.20165019 Date: 2020-08-04 Source: medRxiv

    BACKGROUND: Seroreactivity against human endemic coronaviruses has been linked to disease MESHD severity after SARS-CoV-2 infection MESHD. Assays that are capable of concomitantly detecting antibodies SERO against endemic coronaviridae such as OC43, 229E, NL63, and SARS-CoV-2 may help to elucidate this question. We set up a platform for serum SERO-screening and developed a bead-based Western blot system, namely DigiWest, capable of running hundreds of assays using microgram amounts of protein prepared directly from different viruses. METHODS: The parallelized and miniaturised DigiWest assay was adapted for detecting antibodies SERO using whole protein extract prepared from isolated SARS-CoV-2 virus particles. After characterisation and optimization of the newly established test, whole virus lysates of OC43, 229E, and NL63 were integrated into the system. RESULTS: The DigiWest-based immunoassay SERO system for detection of SARS-CoV-2 specific antibodies SERO shows a sensitivity SERO of 87.2 % and diagnostic specificity of 100 %. Concordance analysis with the SARS-CoV-2 immunoassays SERO available by Roche, Siemens, and Euroimmun indicates a comparable assay performance SERO (Cohen's Kappa ranging from 0.8799-0.9429). In the multiplexed assay, antibodies SERO against the endemic coronaviruses OC43, 229E, and NL63 were detected, displaying a high incidence of seroreactivity against these coronaviruses. CONCLUSION: The DigiWest-based immunoassay SERO, which uses authentic antigens from isolated virus particles, is capable of detecting individual serum SERO responses against SARS-CoV-2 with high specificity and sensitivity SERO in one multiplexed assay. It shows high concordance with other commercially available serologic assays. The DigiWest approach enables a concomitant detection of antibodies SERO against different endemic coronaviruses and will help to elucidate the role of these possibly cross-reactive antibodies SERO.

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MeSH Disease
Human Phenotype

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