A CT radiomics–based random forest model was proven useful for differentiating bone islands from osteoblastic metastases at abdominal CT and showed better diagnostic performance compared with an in... Background It is important to diagnose sclerotic bone lesions in order to determine treatment strategy. Purpose To evaluate the diagnostic performance of a CT radiomics–based machine learning model...
We compared the characteristics of the most cited, most downloaded, and most mentioned (the highest Altmetric Attention Score) articles published in general medical journals. We identified the 640 most frequently cited, 662 most frequently downloaded, and 652 most mentioned articles from 48 general medical journals. A comparison was made of the following characteristics of articles in the most cited, most downloaded, and most mentioned articles: medical specialty, publication type, country of origin, year of publication, and accessibility. There was only a 2.5% overlap in these three groups. Original articles were the more frequent among the most mentioned articles, whereas reviews, case reports, and guidelines/consensus statements were more frequent among the most downloaded articles. The most cited articles were more frequently published in 2010 and before, whereas the most downloaded articles were published in 2017−2018. The most mentioned articles were more frequently open-access articles, compared to the most downloaded articles. The most cited were more frequently older, the most downloaded were more frequently recent and educational, and the most mentioned were more frequently original and open-access articles. The results of our study may provide insights into various measures of article impact.
The novel coronavirus disease 2019 (COVID-19) is a global pandemic. This study’s aim was to identify and characterize the top 100 COVID-19-related scientific publications, which had received the highest Altmetric Attention Scores (AASs). Hence, we searched Altmetric Explorer using search terms such as “COVID” or “COVID-19” or “Coronavirus” or “SARS-CoV-2” or “nCoV” and then selected the top 100 articles with the highest AASs. For each article identified, we extracted the following information: the overall AAS, publishing journal, journal impact factor (IF), date of publication, language, country of origin, document type, main topic, and accessibility. The top 100 articles most frequently were published in journals with high (>10.0) IF (n = 67), were published between March and July 2020 (n = 67), were written in English (n = 100), originated in the United States (n = 45), were original articles (n = 59), dealt with treatment and clinical manifestations (n = 33), and had open access (n = 98). Our study provides important information pertaining to the dissemination of scientific knowledge about COVID-19 in online media.