摘要
一位新闻记者兼机器人与机器学习的工作人员新闻编辑每日新闻-人工智能的新研究是一篇报道的主题。根据NewsRx记者从哥伦比亚卡利发回的新闻报道，研究表明，“创伤性脑损伤(TBI)已经成为全世界残疾的主要来源，增加了使用人工智能(AI)优化成像研究、预后估计、在这项研究中，我们对人工智能中创伤性脑损伤的主要用途进行了文献计量分析和迷你回顾。我们的新闻编辑从Valle大学的研究中获得了一句话，"为本评论提供信息的结果来自截至2023年6月15日的Scopus数据库搜索。文献计量分析是通过Mapping Bibliogr Aphic Metrics方法进行的。知识映射是在VOSviewer软件(V1.6 .18)中进行的，基于Keywor DS的共现分析网络的'链接强度'国家合著者和合引作者。在小型综述部分，我们重点介绍了这些研究的主要发现和贡献。2000年至2023年，共确定495篇科学出版物，2013年以来共发表9262篇引文。在确定的160种期刊中，《神经创伤杂志》、《神经病学前沿》、《神经病学前沿》、《神经病学》、《神经学前沿》、《神经学》、Plos One和Plos One，其中有最多的共被引用。最常出现的关键词是：‘机器学习’、‘深度学习’、‘磁共振成像’和‘颅内压’。美国的合作比任何其他国家都多，其次是英国和中国。发现了四个共被引用的作者群，前20篇论文分为评论和原创文章。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Artificial Intelligenc e is the subject of a report. According to news reporting originating from Cali, Colombia, by NewsRx correspondents, research stated, “Traumatic brain injury (T BI) has become a major source of disability worldwide, increasing the interest i n algorithms that use Artificial Intelligence (AI) to optimize the interpretatio n of imaging studies, prognosis estimation, and critical care issues. In this st udy we present a bibliometric analysis and Mini Review on the main uses that hav e been developed for TBI in AI.” Our news editors obtained a quote from the research from the University of Valle , “The results informing this review come from a Scopus database search as of Ap ril 15, 2023. The bibliometric analysis was carried out via the mapping bibliogr aphic metrics method. Knowledge mapping was made in the VOSviewer software (V1.6 .18), analyzing the ‘link strength’ of networks based on co-occurrence of keywor ds, countries co-authorship and co-cited authors. In the mini-review section, we highlight the main findings and contributions of the studies. A total of 495 sc ientific publications were identified from 2000 to 2023, with 9262 citations pub lished since 2013. Among the 160 journals identified, The Journal of Neurotrauma , Frontiers in Neurology, and Plos One where those with the greatest number of p ublications. The most frequently co-occurring keywords were: ‘machine learning’, ‘deep learning’, ‘magnetic resonance imaging’, and ‘intracranial pressure’. The United States accounted for more collaborations than any other country, followe d by United Kingdom and China. Four co-citation author clusters were found, and the top 20 papers were divided into reviews and original articles.”
NETL
NSTL