Abstract
Most of the existing chest X-ray datasets include labels from a list of findings without specifying their locations on the radiographs. This limits the development of machine learning ...algorithms for the detection and localization of chest abnormalities. In this work, we describe a dataset of more than 100,000 chest X-ray scans that were retrospectively collected from two major hospitals in Vietnam. Out of this raw data, we release 18,000 images that were manually annotated by a total of 17 experienced radiologists with 22 local labels of rectangles surrounding abnormalities and 6 global labels of suspected diseases. The released dataset is divided into a training set of 15,000 and a test set of 3,000. Each scan in the training set was independently labeled by 3 radiologists, while each scan in the test set was labeled by the consensus of 5 radiologists. We designed and built a labeling platform for DICOM images to facilitate these annotation procedures. All images are made publicly available in DICOM format along with the labels of both the training set and the test set.
The COVID-19 pandemic has imposed a heavy burden on health care systems and governments. Health literacy (HL) and eHealth literacy (as measured by the eHealth Literacy Scale eHEALS) are recognized as ...strategic public health elements but they have been underestimated during the pandemic. HL, eHEALS score, practices, lifestyles, and the health status of health care workers (HCWs) play crucial roles in containing the COVID-19 pandemic.
The aim of this study is to evaluate the psychometric properties of the eHEALS and examine associations of HL and eHEALS scores with adherence to infection prevention and control (IPC) procedures, lifestyle changes, and suspected COVID-19 symptoms among HCWs during lockdown.
We conducted an online survey of 5209 HCWs from 15 hospitals and health centers across Vietnam from April 6 to April 19, 2020. Participants answered questions related to sociodemographics, HL, eHEALS, adherence to IPC procedures, behavior changes in eating, smoking, drinking, and physical activity, and suspected COVID-19 symptoms. Principal component analysis, correlation analysis, and bivariate and multivariate linear and logistic regression models were used to validate the eHEALS and examine associations.
The eHEALS had a satisfactory construct validity with 8 items highly loaded on one component, with factor loadings ranked from 0.78 to 0.92 explaining 76.34% of variance; satisfactory criterion validity as correlated with HL (ρ=0.42); satisfactory convergent validity with high item-scale correlations (ρ=0.80-0.84); and high internal consistency (Cronbach α=.95). HL and eHEALS scores were significantly higher in men (unstandardized coefficient B=1.01, 95% CI 0.57-1.45, P<.001; B=0.72, 95% CI 0.43-1.00, P<.001), those with a better ability to pay for medication (B=1.65, 95% CI 1.25-2.05, P<.001; B=0.60, 95% CI 0.34-0.86, P<.001), doctors (B=1.29, 95% CI 0.73-1.84, P<.001; B 0.56, 95% CI 0.20-0.93, P=.003), and those with epidemic containment experience (B=1.96, 95% CI 1.56-2.37, P<.001; B=0.64, 95% CI 0.38-0.91, P<.001), as compared to their counterparts, respectively. HCWs with higher HL or eHEALS scores had better adherence to IPC procedures (B=0.13, 95% CI 0.10-0.15, P<.001; B=0.22, 95% CI 0.19-0.26, P<.001), had a higher likelihood of healthy eating (odds ratio OR 1.04, 95% CI 1.01-1.06, P=.001; OR 1.04, 95% CI 1.02-1.07, P=.002), were more physically active (OR 1.03, 95% CI 1.02-1.03, P<.001; OR 1.04, 95% CI 1.03-1.05, P<.001), and had a lower likelihood of suspected COVID-19 symptoms (OR 0.97, 95% CI 0.96-0.98, P<.001; OR 0.96, 95% CI 0.95-0.98, P<.001), respectively.
The eHEALS is a valid and reliable survey tool. Gender, ability to pay for medication, profession, and epidemic containment experience were independent predictors of HL and eHEALS scores. HCWs with higher HL or eHEALS scores had better adherence to IPC procedures, healthier lifestyles, and a lower likelihood of suspected COVID-19 symptoms. Efforts to improve HCWs' HL and eHEALS scores can help to contain the COVID-19 pandemic and minimize its consequences.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Research in adaptive control algorithms for safety-critical applications is primarily motivated by the fact that these algorithms have the capability to suppress the effects of adverse conditions ...resulting from exogenous disturbances, imperfect dynamical system modelling, degraded modes of operation, and changes in system dynamics. Although government and industry agree on the potential of these algorithms in providing safety and reducing vehicle development costs, a major issue is the inability to achieve a-priori, user-defined performance guarantees with adaptive control algorithms. In this paper, a new model reference adaptive control architecture for uncertain dynamical systems is presented to address disturbance rejection and uncertainty suppression. The proposed framework is predicated on a set-theoretic adaptive controller construction using generalised restricted potential functions.The key feature of this framework allows the system error bound between the state of an uncertain dynamical system and the state of a reference model, which captures a desired closed-loop system performance, to be less than a-priori, user-defined worst-case performance bound, and hence, it has the capability to enforce strict performance guarantees. Examples are provided to demonstrate the efficacy of the proposed set-theoretic model reference adaptive control architecture.
In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to the implementation of adaptive control with a large ...adaptive gain so as to reduce the tracking error rapidly. However, a large adaptive gain can lead to high-frequency oscillations which can adversely affect robustness. A new adaptive law, called optimal control modification, is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations. The modification is based on a minimization of the L2 norm of the tracking error bounded away from some lower bound, formulated as an optimal control problem. The optimality condition is used to derive the modification based on the Pontryagin’s Minimum Principle. The optimal control modification is shown to improve robustness of the standard MRAC without significantly compromising the tracking performance. Flight control simulations demonstrate the effectiveness of the new adaptive law. A series of recent, successful flight tests of this adaptive law on a NASA F/A-18A aircraft at NASA Dryden Flight Research Center further demonstrate the effectiveness of the optimal control modification adaptive law.
ObjectivesWe examined impacts and interactions of COVID-19 response involvement, health-related behaviours and health literacy (HL) on anxiety, depression, and health-related quality of life (HRQoL) ...among healthcare workers (HCWs).DesignA cross-sectional study was conducted. Data were collected 6 April to 19 April 2020 using online-based, self-administered questionnaires.Setting19 hospitals and health centres in Vietnam.Participants7 124 HCWs aged 21–60 years.ResultsThe COVID-19 response-involved HCWs had higher anxiety likelihood (OR (95% CI)=4.41 (3.53 to 5.51)), higher depression likelihood (OR(95% CI)=3.31 (2.71 to 4.05)) and lower HRQoL score (coefficient, b(95% CI)=−2.14 (−2.89 to −1.38)), compared with uninvolved HCWs. Overall, HCWs who smoked or drank at unchanged/increased levels had higher likelihood of anxiety, depression and lower HRQoL scores; those with unchanged/healthier eating, unchanged/more physical activity and higher HL scores had lower likelihood of anxiety, depression and higher HRQoL scores. In comparison to uninvolved HCWs who smoked or drank at never/stopped/reduced levels, involved HCWs with unchanged/increased smoking or drinking had lower anxiety likelihood (OR(95% CI)=0.34 (0.14 to 0.83)) or (OR(95% CI)=0.26 (0.11 to 0.60)), and lower depression likelihood (OR(95% CI)=0.33 (0.15 to 0.74)) or (OR(95% CI)=0.24 (0.11 to 0.53)), respectively. In comparison with uninvolved HCWs who exercised at never/stopped/reduced levels, or with those in the lowest HL quartile, involved HCWs with unchanged/increased exercise or with one-quartile HL increment reported lower anxiety likelihood (OR(95% CI)=0.50 (0.31 to 0.81)) or (OR(95% CI)=0.57 (0.45 to 0.71)), lower depression likelihood (OR(95% CI)=0.40 (0.27 to 0.61)) or (OR(95% CI)=0.63 (0.52 to 0.76)), and higher HRQoL scores (b(95% CI)=2.08 (0.58 to 3.58)), or (b(95% CI)=1.10 (0.42 to 1.78)), respectively.ConclusionsPhysical activity and higher HL were found to protect against anxiety and depression and were associated with higher HRQoL. Unexpectedly, smoking and drinking were also found to be coping behaviours. It is important to have strategic approaches that protect HCWs’ mental health and HRQoL.
A simple metal-free method for the synthesis of quinazolinones from commercially available 2-nitrobenzyl alcohols and tetrahydroisoquinolines is developed. The reaction conditions were tolerant of an ...array of functionalities such as halogen, tertiary amine, protected alcohol, and ester groups. Under nearly identical conditions, quinazolinethiones were obtained in the presence of elemental sulfur and suitable mediators.
•EndoCV2020, an endoscopy computer vision challenge addresses eminent problems in endoscopy.•Deep learning methods built to address artefacts and disease categories.•Comprehensive dataset comprising ...multi-center, multi-organ, multi-modal and multi-class.•Over 47,000 annotations and 3440 frames publicly released.•Detection and segmentation algorithms are devised, compared and dissected.•Hypothesis formulated to identify the gaps in current methods.
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The Endoscopy Computer Vision Challenge (EndoCV) is a crowd-sourcing initiative to address eminent problems in developing reliable computer aided detection and diagnosis endoscopy systems and suggest a pathway for clinical translation of technologies. Whilst endoscopy is a widely used diagnostic and treatment tool for hollow-organs, there are several core challenges often faced by endoscopists, mainly: 1) presence of multi-class artefacts that hinder their visual interpretation, and 2) difficulty in identifying subtle precancerous precursors and cancer abnormalities. Artefacts often affect the robustness of deep learning methods applied to the gastrointestinal tract organs as they can be confused with tissue of interest. EndoCV2020 challenges are designed to address research questions in these remits. In this paper, we present a summary of methods developed by the top 17 teams and provide an objective comparison of state-of-the-art methods and methods designed by the participants for two sub-challenges: i) artefact detection and segmentation (EAD2020), and ii) disease detection and segmentation (EDD2020). Multi-center, multi-organ, multi-class, and multi-modal clinical endoscopy datasets were compiled for both EAD2020 and EDD2020 sub-challenges. The out-of-sample generalization ability of detection algorithms was also evaluated. Whilst most teams focused on accuracy improvements, only a few methods hold credibility for clinical usability. The best performing teams provided solutions to tackle class imbalance, and variabilities in size, origin, modality and occurrences by exploring data augmentation, data fusion, and optimal class thresholding techniques.
Background: The COVID-19 pandemic has been disseminating fear in the community, which has affected people’s quality of life, especially those with health problems. Health literacy (HL), eHealth ...literacy (eHEAL), and digital healthy diet literacy (DDL) may have potential impacts on containing the pandemic and its consequences. This study aimed to examine the association between the fear of COVID-19 scale (FCoV-19S) and the health-related quality of life (HRQoL), and to examine the effect modification by HL, eHEAL, and DDL on this association. Methods: A cross-sectional study was conducted in 11 hospitals across Vietnam from 7 April to 31 May 2020. Data were collected on 4348 outpatients, including demographic characteristics, HL, eHEAL, DDL, FCoV-19S, and HRQoL. Multiple linear regression and interaction models were used to explore associations. Results: Patients with higher FCoV-19S scores had lower HRQoL scores (unstandardized coefficient, B = −0.78, p < 0.001). HL (B = 0.20, p < 0.001), eHEAL (B = 0.24, p < 0.001), and DDL (B = 0.20, p < 0.001) were positively associated with higher HRQoL scores. The negative impact of FCoV-19S on HRQoL was significantly attenuated by higher eHEAL score groups (from one standard deviation (SD) below the mean, B = −0.93, p < 0.001; to the mean, B = −0.85, p < 0.001; and one SD above the mean, B = −0.77, p < 0.001); and by higher DDL score groups (from one SD below the mean, B = −0.92, p < 0.001; to the mean, B = −0.82, p < 0.001; and one SD above the mean, B = −0.72, p < 0.001). Conclusions: eHealth literacy and digital healthy diet literacy could help to protect patients’ health-related quality of life from the negative impact of the fear of COVID-19 during the pandemic.
Talaromyces marneffei
is a dimorphic fungus that causes substantial disease in Asia, especially among persons infected with the human immunodeficiency virus. In this randomized, controlled trial, ...initial therapy with amphotericin B was found to be superior to itraconazole.
The dimorphic fungus
Talaromyces
(previously
Penicillium
)
marneffei
causes a life-threatening mycosis in immunocompromised persons living in or traveling to Southeast Asia, China, and India.
1
Talaromycosis (previously penicilliosis) is a major cause of human immunodeficiency virus (HIV)–related death; its prevalence is surpassed only by the prevalence of tuberculosis and cryptococcosis,
2
and it leads to 4 to 15% of HIV-related hospital admissions in regions in which the disease is endemic.
3
–
7
Talaromycosis is increasingly diagnosed among patients who are not infected with HIV but who have other immunodeficiency conditions
8
and is reported to be the second most common cause of all . . .
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•9′-Methoxypinoresinol, calofurfuralside A, and calofurfuralside B were isolated from C. gigantea.•9′-Methoxypinoresinol showed the cytotoxicity against PANC-1 cells with an IC50 ...value of 3.7μM.•9′-Methoxypinoresinol significantly inhibited the colony formation of PANC-1 cells.
A new lignan, 9′-methoxypinoresinol (1), and two new glycosylated 5-hydroxymethylfurfurals, calofurfuralside A (2), and calofurfuralside B (3), together with nine known compounds (4–12) have been isolated from the active fractions, CHCl3 (IC50, 0.32μgmL−1) and EtOAc (IC50, 0.55μgmL−1) fractions of the leaves of Calotropis gigantea. Their structures were elucidated based on NMR and MS data. Among the isolated compounds, compounds 1 and 9 exhibited potent cytotoxicity against PANC-1 human pancreatic cancer cell line under the normoglycemic condition with IC50 values of 3.7 and 3.3μM, respectively. 9′-Methoxypinoresinol (1) significantly inhibited the colony formation of PANC-1 cells in a concentration-dependent manner.
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