TY - JOUR AU - Abd-Alrazaq, Alaa AU - Schneider, Jens AU - Mifsud, Borbala AU - Alam, Tanvir AU - Househ, Mowafa AU - Hamdi, Mounir AU - Shah, Zubair PY - 2021 DA - 201/3/8 TI - COVID-19文献综述:机器上优于文献计量分析乔- J地中海互联网Res SP - e23703六世- 23 - 3 KW -新型冠状病毒病KW - COVID-19 KW - SARS-CoV-2 KW - 2019 KW - ncov千瓦文献分析——文学KW——机器学习KW -研究KW -审查AB -背景:COVID-19的出现后不久,研究人员迅速动员研究的许多方面疾病如进化,临床表现、效果、治疗和疫苗。这导致与covid -19相关的出版物数量迅速增加。对于如此大的领域，使用传统的评审方法(例如，范围界定和系统评审)确定趋势和感兴趣的领域是具有挑战性的。目的:我们旨在进行广泛的文献计量学分析，以提供COVID-19文献的全面概述。方法:我们使用COVID-19开放研究数据集(CORD-19)，该数据集包含大量与所有冠状病毒相关的研究文章。我们使用基于机器学习的方法来分析最相关的covid -19相关文章，并提取最突出的主题。具体而言，我们采用聚类算法，根据文章摘要的相似度对已发表的文章进行分组，以识别研究热点和当前的研究方向。我们已经通过GitHub向社区开放了我们的软件。结果:从数据库中检索到的196,630篇出版物中，我们将28,904篇纳入了分析。 The mean number of weekly publications was 990 (SD 789.3). The country that published the highest number of COVID-19–related articles was China (2950/17,270, 17.08%). The highest number of articles were published in bioRxiv. Lei Liu affiliated with the Southern University of Science and Technology in China published the highest number of articles (n=46). Based on titles and abstracts alone, we were able to identify 1515 surveys, 733 systematic reviews, 512 cohort studies, 480 meta-analyses, and 362 randomized control trials. We identified 19 different topics covered among the publications reviewed. The most dominant topic was public health response, followed by clinical care practices during the COVID-19 pandemic, clinical characteristics and risk factors, and epidemic models for its spread. Conclusions: We provide an overview of the COVID-19 literature and have identified current hotspots and research directions. Our findings can be useful for the research community to help prioritize research needs and recognize leading COVID-19 researchers, institutes, countries, and publishers. Our study shows that an AI-based bibliometric analysis has the potential to rapidly explore a large corpus of academic publications during a public health crisis. We believe that this work can be used to analyze other eHealth-related literature to help clinicians, administrators, and policy makers to obtain a holistic view of the literature and be able to categorize different topics of the existing research for further analyses. It can be further scaled (for instance, in time) to clinical summary documentation. Publishers should avoid noise in the data by developing a way to trace the evolution of individual publications and unique authors. SN - 1438-8871 UR - //www.mybigtv.com/2021/3/e23703 UR - https://doi.org/10.2196/23703 UR - http://www.ncbi.nlm.nih.gov/pubmed/33600346 DO - 10.2196/23703 ID - info:doi/10.2196/23703 ER -