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1.
Journal of the American Academy of Dermatology ; 87(3):AB204, 2022.
Article in English | EMBASE | ID: covidwho-2031397

ABSTRACT

A highly visual practice, dermatology as a field has significant potential to use emerging technology such as mobile applications for research and patient-centered mapping of the disease process. The UCSF team is working to create SkinTracker, a mobile application for patients with skin disease to remotely participate in clinical trials and research studies. The initial iteration of the application focuses on atopic dermatitis. The application includes an enrollment and consent module, validated surveys including the Patient Oriented Eczema Measure (POEM), Dermatology Life Quality Index (DLQI), Numerical Rating Scale (NRS) for itch, link to a wearable device that collects biometric data, a voice diary, and a patient-directed photography module to facilitate physician evaluation of disease. Also included is the ability to report medication use, adverse events, and the ability to chat with the study team. The patient information is available to the research team on a secure online website, where researchers can assess patient photographs to perform Eczema Area and Severity Index (EASI) scoring, note important patient observations from the voice diary, and view quantitative data from both patient surveys and health measures like physical activity, sleep, and environmental factors. We believe this application and website will facilitate patient interest and participation in research, continue research despite in-person restrictions placed during the COVID-19 pandemic, and allow enrollment of more diverse patients for clinical studies who would otherwise be less likely to participate in research due to time or financial constraints.

2.
2021 Ieee 6th International Conference on Big Data Analytics ; : 9-13, 2021.
Article in English | Web of Science | ID: covidwho-1324942

ABSTRACT

Since the outbreak of the COVID-19, small and medium-sized enterprises have been greatly affected. In order to cope with the difficulty of capital turnover for small and medium-sized enterprises, the government has successively introduced a series of financial policies to increase credit support and reduce financing costs. The rapid development of technology has also prompted further innovations in the operating models of banks and other credit platforms. However, banks and credit platforms must consider practical issues such as their own capital costs and risk assessment while they help small and medium-sized enterprises reduce financing costs. This paper aims to study and design a credit risk assessment system based on big data technology and machine learning algorithms. It is hoped that the system will enhance the bank's ability to identify the credit risks of small and medium-sized enterprises, so as to solve the problem of difficult and expensive financing for small and medium-sized enterprises. At the same time, it will reduce the bank's own bad loan ratio and increase profit margins. Achieving a win-win situation for small and medium-sized enterprises and banks, it's crucial to promote jointly the development of economy.

3.
2021 World Wide Web Conference, WWW 2021 ; : 2590-2600, 2021.
Article in English | Scopus | ID: covidwho-1280481

ABSTRACT

Since late December 2019, it has been reported an outbreak of atypical pneumonia, now known as COVID-19 caused by the novel coronavirus. Cases have spread to more than 200 countries and regions internationally. World Health Organization (WHO) officially declares the coronavirus outbreak a pandemic and the public health emergency has caused world-wide impact to daily lives: people are advised to keep social distance, in-person events have been moved online, and some function facilitates have been locked-down. Alternatively, the Web becomes an active venue for people to share information. With respect to the on-going topic, people continuously post questions online and seek for answers. Yet, sharing global information conveyed in different languages is challenging because the language barrier is intrinsically unfriendly to monolingual speakers. In this paper, we propose a multilingual COVID-QA model to answer people's questions in their own languages while the model is able to absorb knowledge from other languages. Another challenge is that in most cases, the information to share does not have parallel data in multiple languages. To this end, we propose a novel framework which incorporates (unsupervised) translation alignment to learn as pseudo-parallel data. Then we train multilingual question-answering mapping and generation. We demonstrate the effectiveness of our proposed approach compared against a series of competitive baselines. In this way, we make it easier to share global information across the language barriers, and hopefully we contribute to the battle against COVID-19. © 2021 ACM.

4.
Journal of Thoracic Oncology ; 16(3):S428-S429, 2021.
Article in English | EMBASE | ID: covidwho-1161061

ABSTRACT

Introduction: COVID-19, a disease caused by coronavirus SARS-CoV-2, has drawn public attention worldwide. The virus is also associated with carcinogenesis. Epstein-Barr virus (EBV) was reported to be related to pulmonary lymphoepithelioma-like carcinoma (PLELC), a rare subtype of non-small cell lung cancer (NSCLC). However, the understanding of the treatment for EBV-infected NSCLC was still elusive. Immunotherapy that targets PD-1/PD-L1 has been utilized as a novel clinical treatment in recent years. Here, we focus on the genomic landscapes of lung cancers with EBV-infection and its correlation with PD-L1. Methods: Patients with both PD-L1 expression detection and genomic information were screened in HapLab database. HaploX 605-gene panel sequencing, covering 1.31 MB genome, was performed to analyze the genomic data of patients. PD-L1 expression was detected by immunochemistry. Bioinformatic analysis of genomic mutations and the correlation with the expression of PD-L1 were studied. Results: We analyzed the genomic profiles of 23 EBV-infected NSCLC patients. 11 cases of lung squamous-cell carcinoma (LUSC), 4 cases of lung adenocarcinoma (LUAD), 5 cases of lung pulmonary lymphoepithelioma-like carcinoma (PLELC), and 3 unidentified cases were included in this study. Collectively, 93 genome mutations of 67 genes were detected in 23 EBV-infection cases. Top 3 frequently mutated genes were TP53 (27%), CSMD3 (18%) and KMT2D (18%). The EBV-infected patients exhibited a low level of tumor mutation burden (TMB). The median TMB was 1.53 Muts/MB (ranging from 0 to 14.5 Muts/MB). Only 3 of 23 patients (13.0%) harbored the canonical driver mutations in NSCLC. Interestingly, 10/23 patients (43.5%) showed high expression of PD-L1, while 13/23 patients (56.5%) showed low expression. We also assessed the expression of PD-L1 in lung cancers with no EBV-infection (867 cases). Only 118/867 (13.6%) patients without EBV-infection presented high PD-L1 expression, while 749/867 (86.4%) presented low PD-L1 expression. Conclusion: EBV-infection can occur in different kinds of NSCLC, including LUSC, LUAD, and PLELC. TMB and driver mutations of EBV-infected NSCLC were not frequently observed as normal lung cancers, implying a different mechanism leading to EBV-infected lung cancers. Interestingly, EBV-infected NSCLC tended to have a high correlation with the expression of PD-L1. This may give a hint on the application of checkpoint blockade immunotherapy on EBV-infected NSCLC. [Formula presented] Keywords: Epstein-Barr virus (EBV), PD-L1 expression, non-small cell lung cancer (NSCLC)

5.
Journal of Public Budgeting, Accounting and Financial Management ; 2020.
Article in English | Scopus | ID: covidwho-913404

ABSTRACT

Purpose: The authors examine the Taiwanese government's budgetary responses to COVID-19, with a focus on the special budgets created for containing the virus, undertaking bailouts and providing economic stimulus. The authors assess the short-term and long-term fiscal implications of the budgetary measures and discuss how Taiwan's experiences could provide lessons for other countries for future emergencies. Design/methodology/approach: The authors collect data from Taiwan's official documents and news reports and compare the special budgets proposed by the Taiwanese government during the Great Recession and the COVID-19 pandemic. The authors discuss lessons learned from the 2008–09 special budget and possible concerns of the 2020 special budgets. In the conclusions, the authors discuss potential long-term implications for Taiwan's budgetary system as well as possible lessons for other countries based on Taiwan's experiences Findings: The authors found that the 2008–09 special budgets focused only on economic stimulus, whereas the 2020 special budgets covered COVID-19 treatments, bailouts and economic stimulus. In 2020, the Taiwanese government devised targeted bailout plans for industries and individuals most affected by the pandemic and created the Triple Stimulus Vouchers to boost the economy. Since the special budgets were largely funded through borrowing, the authors pointed out concerns for fiscal sustainability and intergenerational equity. Originality/value: COVID-19 has changed how the world functions massively. This work adds to the literature on COVID-19 by providing Taiwan's budgetary responses to the pandemic. This work also identifies ways for Taiwan to improve the existing budgetary system and discusses lessons for other countries. © 2020, Emerald Publishing Limited.

6.
Hong Kong Med J ; 27(1): 7-17, 2021 02.
Article in English | MEDLINE | ID: covidwho-732655

ABSTRACT

BACKGROUND: Multicentre cohort investigations of patients with coronavirus disease 2019 (COVID-19) have been limited. We investigated the clinical and chest computed tomography characteristics of patients with COVID-19 at the peak of the epidemic from multiple centres in China. METHODS: We retrospectively analysed the epidemiologic, clinical, laboratory, and radiological characteristics of 189 patients with confirmed COVID-19 who were admitted to seven hospitals in four Chinese provinces from 18 January 2020 to 3 February 2020. RESULTS: The mean patient age was 44 years and 52.9% were men; 186/189 had ≥1 co-existing medical condition. Fever, cough, fatigue, myalgia, diarrhoea, and headache were common symptoms at onset; hypertension was the most common co-morbidity. Common clinical signs included dyspnoea, hypoxia, leukopenia, lymphocytopenia, and neutropenia; most lesions exhibited subpleural distribution. The most common radiological manifestation was mixed ground-glass opacity with consolidation (mGGO-C); most patients had grid-like shadows and some showed paving stones. Patients with hypertension, dyspnoea, or hypoxia exhibited more severe lobe involvement and diffusely distributed lesions. Patients in severely affected areas exhibited higher body temperature; more fatigue and dyspnoea; and more manifestations of multiple lesions, lobe involvement, and mGGO-C. During the Wuhan lockdown period, cough, nausea, and dyspnoea were alleviated in patients with newly confirmed COVID-19; lobe involvement was also improved. CONCLUSIONS: Among patients with COVID-19 hospitalised at the peak of the epidemic in China, fever, cough, and dyspnoea were the main symptoms at initial diagnosis, accompanied by lymphocytopenia and hypoxaemia. Patients with severe disease showed more severe lobe involvement and diffuse pulmonary lesion distribution.


Subject(s)
COVID-19/diagnostic imaging , Pneumonia, Viral/diagnostic imaging , Radiography, Thoracic , Tomography, X-Ray Computed , Adult , COVID-19/epidemiology , China/epidemiology , Comorbidity , Female , Hospitalization , Humans , Male , Pneumonia, Viral/epidemiology , Pneumonia, Viral/virology , Retrospective Studies , SARS-CoV-2 , Severity of Illness Index
7.
Zhonghua Yi Xue Za Zhi ; 100(16): 1223-1229, 2020 Apr 28.
Article in Chinese | MEDLINE | ID: covidwho-326498

ABSTRACT

Objective: To construct and evaluate a diagnosis pathway (Xiangya pathway) for Corona Virus Disease 2019 (COVID-19). Methods: Consecutive subjects aged ≥12 years old who were screened for COVID-19 were included in Xiangya Hospital of Central South University from January 23 to February 3, 2020, and the subjects were further divided into the inception cohort and the validation cohort. The gender, age, onset time of disease of the subjects were recorded. The information of epidemiological history, fever, and the declined blood lymphocytes were collected as clinical indicators, CT scan was used to evaluate the possibility of COVID-19 and range of lung involvement. According to the current Chinese national standards, throat swabs of suspected cases were collected and the nucleic acid of COVID-19 was detected by reverse transcription-polymerase chain reaction (RT-PCR). The Xiangya pathway was constructed with multi-indexes, compared with clinical indicators, CT results and Chinese national standards, their effectiveness of detecting confirmed cases were verified in the inception and validation cohort. Results: A total of 382 consecutive adults who was screened for COVID-19 were included, and 261 cases were in the inception cohort and 121 cases were in the validation cohort. Among the 382 cases, 192 were males (50.3%) and 190 were females (49.7%), with a median age of 35 years (range: 15-92 years). There were 183 cases (47.9%) with epidemiological history, 275 cases (72.0%) with fever, 212 cases (55.5%) with decreased peripheral blood lymphocytes, 114 cases (29.8%) with positive CT findings, 43 cases (11.3%) with positive CT-COVID-19, and 30 cases (7.9%) with positive virus nucleic acid by throat swab. Compared with clinical indicators, the sensitivity and specificity of CT were 0.950 and 0.704, respectively. The accuracy of CT to make a definite diagnosis was higher than that of epidemiological history, fever, and declined blood lymphocyte count (0.809 vs 0.660, 0.532, 0.596, P=0.001, 0.002, 0.003, respectively). The sensitivity of this pathway and the pathway recommended by the Health Commission of China were both high (all were 1.000), while the specificity and accuracy of the Xiangya pathway were higher than the one recommended by the Health Commission (0.872 vs 0.765, 0.778 vs 0.592, both P<0.001). The CT-COVID-19 reduced the missed diagnosis rate caused by false negative of nucleic acid test (31 vs 64), with difference rate of 51.6%, and the positive rate of nucleic acid test was 64.5% (20/31). In validation cohort, the specificity and accuracy of the Xiangya pathway was 0.967, the positive rate of nucleic acid test was 76.9%(10/13). Conclusions: The Xiangya pathway can predict the nucleic acid test results of COVID-19, and can be applied as a reliable strategy to screen patients with suspected COVID-19 among people aged ≥12 years in areas other than Hubei during the epidemic period of COVID-19. The cohort size needs to be increased for further validation.


Subject(s)
Betacoronavirus , Coronavirus Infections , Pandemics , Pneumonia, Viral , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19 , COVID-19 Testing , China , Clinical Laboratory Techniques , Coronavirus Infections/diagnosis , Female , Humans , Male , Middle Aged , Pneumonia, Viral/diagnosis , SARS-CoV-2 , Young Adult
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