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2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021 ; : 328-333, 2021.
Article in English | Scopus | ID: covidwho-1722889


The worldwide spread of COVID-19 has made a severe impact on human health and life. It has shown rapid propagation, long in vitro survival, and a long incubation period. More seriously, COVID-19 is more susceptible to variation, as it is an RNA virus. Mutations of COVID-19 have been reported in multiple countries worldwide, which makes drug and vaccine development a significant challenge. To search for potential drugs and vaccines and reveal the atlas of COVID-19 evolution, we extract information from massive unstructured data and construct a COVID-19 knowledge graph using the COVID-19 data. Based on machine learning approaches, we infer and predict novel coronavirus pneumonia-related diseases, drug action targets, etc. to speculate on new and more effective treatment methods. In addition, to study transcriptome of SARS-CoV-2, new ideas can be provided to biomedical experts with flexible responses to viral variation. An in-depth analysis of the COVID-19 pathomechanism at the pharmaceutical, genetic, and protein levels provides effective means and tools for novel coronavirus pneumonia vaccines, drug development, and therapeutic program design. © 2021 IEEE.

Library Hi Tech ; 2021.
Article in English | Scopus | ID: covidwho-1281950


Purpose: The study aims to find out the university students' health information service needs in post-COVID-19 age and then consider how to do the health information services well and promote it in further work. Design/methodology/approach: This study uses Kano model to design a questionnaire about university students' health information service needs from academic library and investigates 243 students from seven universities in China. The data generated were analyzed using a statistical tool and presented in tables. Findings: The results show the students' different requirements level of health information services from academic library as must-be requirements, one-dimensional requirements, attractive quality attributes and indifferent quality in post-COVID-19 age. Research limitations/implications: The questionnaire design and the scale of respondents have limitation, such as only focus on Chinese university, have not characteristically research on different group of students. It could optimize to cover more worldwide university students and refer to different groups of students' needs in further research. Originality/value: The paper expands and deepens the theory about university library health information service and provides a practical reference and proposes some suggestions for academic libraries on how to carry out health information services and give the social health institutions inspiration on how to promote the health services, especially in post-COVID-19 age. © 2021, Emerald Publishing Limited.

Zhonghua Yi Xue Za Zhi ; 100(46): 3702-3705, 2020 Dec 15.
Article in Chinese | MEDLINE | ID: covidwho-993612


Objective: During the COVID-19 pandemic, the electronic "questionnaire star" was employed to investigate the general situation, medication situation and pandemic impact of children diagnosed with asthma in our hospital and enrolled in the electronic platform of the Chinese Children's Asthma Action Plan (CCAAP). The internet technology and big data were used to grasp the trend and asthma control of children who had been at home for a long time due to the pandemic, so as to facilitate the management. Methods: By random cluster sampling survey method, according to the needs and medication adherence score, the electronic "questionnaire star" was designed to conduct a survey among children (0 to 14 years old) who diagnosed with asthma and joined the CCAAP on the basis of bronchial asthma medication adherence scale. Finally, the results of electronic questionnaire survey were analyzed. Results: A total of 423 questionnaires were sent out, 422 of which were valid, with an effective response rate of 99.7%. The results of questionnaire survey showed that 296 cases were male, accounting for 70.1%, and 126 cases were female, accounting for 29.9%, with an average age of (5.4±2.6) years old. The average age of males and females was (5.3±2.6) and (5.4±2.6) years old, respectively. There were more children aged ≥5 years than children who were younger than 5 years. Additionally, 13.95% of the parents thought that the pandemic had more than moderate impact on children with asthma, and 76.12% of the children were in the green zone and had no asthma attack. The proportion of green zone inhaled drugs (79.8%) was higher than yellow zone and red zone (49.8%). After using the CCAAP platform, the dissatisfaction rate was only 1.42%. Moreover, 71.87% of the children's medical expenses decreased, and the proportion of frequent use and intermittent use of antibiotics reduced, however, the proportion of occasional use and never use of antibiotics increased significantly (all P<0.05). The average score of drug compliance was 4.56, and the more frequently the platform was used, the higher the score of medication compliance was (P<0.05). Conclusions: After using CCAAP management with the aid of internet technology, children with asthma who had been isolated at home for a long time were less affected by COVID-19, with high medication compliance, generally lower medical expenses, significantly reduced use of antibiotics, and high satisfaction. This management mode provides a new idea for internet medicine.

Asthma , COVID-19 , Adolescent , Asthma/drug therapy , Child , Child, Preschool , Female , Humans , Infant , Infant, Newborn , Male , Pandemics , SARS-CoV-2 , Surveys and Questionnaires