Corpus overview


MeSH Disease



There are no seroprevalence terms in the subcorpus

    displaying 1 - 2 records in total 2
    records per page

    An Analysis Review, Detection Coronavirus Disease 2019 MESHD ( COVID-19 MESHD) based on Biosensor Application

    Authors: Norhana Arsad; Bakr Taha; Yousif Al Mashhadany

    id:10.20944/preprints202008.0597.v1 Date: 2020-08-27 Source:

    The global spread of coronavirus disease MESHD (COVID -19) worldwide has had a significant effect on social and economic growth. The contamination keeps on advancing quickly and eccentrically, representing a significant test to its recognition and conclusion. Coronaviruses are commonly recognized by seclusion from tests, regardless of whether natural or clinical, utilizing some atomic science procedures, which can take a few days. In this work an analytical review of virus transmission TRANS, methods of diagnosing COVID -19 using artificial intelligence techniques to classify images and types of biosensors. At long last, the deformities MESHD and points of interest of each kind of sensor are recognized and examined. This exploration gives an explanatory audit of the utilization of crown infection COVID-19 MESHD in 2019. Related examinations were led utilizing five dependable databases, for example, Science Direct, IEEE Xplore, Scopus, Web of Science, and PubMed. An acceptable investigation is remembered for this audit, which can be depended upon as a logical database to put resources into another technique for recognizing COIVD-19.

    Knowledge, Attitude and Practice towards COVID-19 MESHD among Patients with Musculoskeletal and Rheumatic Diseases MESHD in Nepal: A Web- based Cross-Sectional Study

    Authors: Dr. Binit Vaidya; Dr. Manisha Bhochhibhoya; Dr. Rikesh Baral; Dr. Shweta Nakarmi

    doi:10.21203/ Date: 2020-04-22 Source: ResearchSquare

    Introduction/objectives: The global health crisis created by Coronavirus Disease MESHD ( COVID-19 MESHD) can be a serious concern to rheumatologists. The relationship of rheumatic diseases MESHD, their therapies, and COVID-19 MESHD with multiple genuine and malicious information available online can influence the knowledge and attitude of rheumatic MESHD patients. This web-based google-form study was conducted to understand the knowledge, attitude and practices of rheumatologic patients towards COVID-19 MESHD in Nepal. Methodology: A web based cross-sectional study was conducted among the patients with rheumatic diseases MESHD. Modified version of questionnaire prepared by Zhong BL et al was used after consent. It was then translated in Nepali language for comprehensibility. The final questionnaire contained a total of 29 questions; 6 for demographic parameters, 12, 5 and 6 for knowledge, attitude and practice behaviors, respectively. Simple descriptive statistics describing the positive responses in each domain. Multiple linear regression analysis done to observe demographic variables associated with the knowledge, attitude and practice. Results: Among 380 participants, 63.2% were female TRANS. Most of the participants were aware of the clinical features of COVID-19 MESHD (91.6 %), 71.5% had positive attitude towards its control, some (31.5 %) thought that they had greater chance of getting COVID-19 MESHD than others and 18.9 % believed that the anti-rheumatic medications could increase their susceptibility to infection. Majority (> 94.7%) practiced preventive measures.Conclusions: Patients with rheumatic diseases MESHD were aware of the general clinical features, route of transmission TRANS and general preventive measures regarding COVID-19 MESHD.

The ZB MED preprint Viewer preVIEW includes all COVID-19 related preprints from medRxiv and bioRxiv, from ChemRxiv, from ResearchSquare, from arXiv and from and is updated on a daily basis (7am CET/CEST).
The web page can also be accessed via API.



MeSH Disease

Export subcorpus as...

This service is developed in the project nfdi4health task force covid-19 which is a part of nfdi4health.

nfdi4health is one of the funded consortia of the National Research Data Infrastructure programme of the DFG.