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排序方式: 共有1495条查询结果,搜索用时 20 毫秒
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Clyde W. Yancy James L. Januzzi Larry A. Allen Javed Butler Leslie L. Davis Gregg C. Fonarow Nasrien E. Ibrahim Mariell Jessup JoAnn Lindenfeld Thomas M. Maddox Frederick A. Masoudi Shweta R. Motiwala J. Herbert Patterson Mary Norine Walsh Alan Wasserman 《Journal of the American College of Cardiology》2018,71(2):201-230
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Alexander Peikert Brian L. Claggett KyungMann Kim Jacob A. Udell Jacob Joseph Akshay S. Desai Michael E. Farkouh Sheila M. Hegde Adrian F. Hernandez Deepak L. Bhatt J. Michael Gaziano H. Keipp Talbot Clyde Yancy Inder Anand Lu Mao Lawton S. Cooper Scott D. Solomon Orly Vardeny 《European journal of heart failure》2023,25(2):299-310
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Background
The use of social media within the medical field has rapidly evolved over the past two decades, with Twitter being one of the most common platforms of engagement. The use of hashtags such as #pedsanes has been reported as a community builder around the subject of pediatric anesthesia. Understanding the use of #pedsanes can inform dissemination of pediatric anesthesia content and discourse. We aimed to describe the distribution and patterns of tweets and contributors using #pedsanes across the globe.Methods
Using Tweetbinder ( https://www.tweetbinder.com ) and the R package “academictwitteR,” we extracted tweets that included the hashtag “#pedsanes” from March 14, 2016 to March 10, 2022. Tweets were analyzed for frequency, type, unique users, impact and reach, language, content, and the most common themes.Results
A total of 58 724 tweets were retrieved; 22 071 (38.8%) were original tweets including 3247 replies, while 35 971 (61.2%) were retweets all generated by over 5946 contributors located in at least 122 countries. The frequency distribution of tweets gradually increased over time with peaks in activity corresponding to major pediatric anesthesia societal meetings and during the early phases of the COVID-19 pandemic. The most retweeted and most liked posts included images.Discussion
We report the widespread and increasing use of social media and the “#pedsanes” hashtag within the pediatric anesthesia and medical community over time. It remains unknown the extent to which Twitter hashtag activity translates to changes in clinical practice. However, the #pedsanes hashtag appears to play a key role in disseminating pediatric anesthesia information globally. 相似文献996.
Clyde Matava Evelina Pankiv Luis Ahumada Benjamin Weingarten Allan Simpao 《Paediatric anaesthesia》2020,30(3):264-268
Artificial intelligence and machine learning are rapidly expanding fields with increasing relevance in anesthesia and, in particular, airway management. The ability of artificial intelligence and machine learning algorithms to recognize patterns from large volumes of complex data makes them attractive for use in pediatric anesthesia airway management. The purpose of this review is to introduce artificial intelligence, machine learning, and deep learning to the pediatric anesthesiologist. Current evidence and developments in artificial intelligence, machine learning, and deep learning relevant to pediatric airway management are presented. We critically assess the current evidence on the use of artificial intelligence and machine learning in the assessment, diagnosis, monitoring, procedure assistance, and predicting outcomes during pediatric airway management. Further, we discuss the limitations of these technologies and offer areas for focused research that may bring pediatric airway management anesthesiology into the era of artificial intelligence and machine learning. 相似文献
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