国际标准期刊号: 2161-119X

耳鼻喉科:开放获取

开放获取

我们集团组织了 3000 多个全球系列会议 每年在美国、欧洲和美国举办的活动亚洲得到 1000 多个科学协会的支持 并出版了 700+ 开放获取期刊包含超过50000名知名人士、知名科学家担任编委会成员。

开放获取期刊获得更多读者和引用
700 种期刊 15,000,000 名读者 每份期刊 获得 25,000 多名读者

索引于
  • 哥白尼索引
  • 谷歌学术
  • 夏尔巴·罗密欧
  • 打开 J 门
  • Genamics 期刊搜索
  • 参考搜索
  • 哈姆达大学
  • 亚利桑那州EBSCO
  • OCLC-世界猫
  • 普布隆斯
  • 日内瓦医学教育与研究基金会
  • ICMJE
分享此页面

抽象的

Analysis of Nursing Safety Incident Characteristics Using Deep LearningBased Medical Data Association Rules Method in ENT Surgery

David Kohrman

Otolaryngology is a fairly current condition, and complications including infection and significant bleeding constantly be during surgery, which pose a serious threat to the cases' mortality. Exploring the distinctive characteristics of postoperative nursing safety events in cases who have experienced otolaryngology surgery and comprehending the distinctive features of postoperative nursing safety events in otolaryngology surgery cases are of utmost significance frequentness of postoperative safety nursing incidents were linked by this study's preoperative safety protection for 385 convalescents. According to this study, the main factors impacting postoperative care are erected lesions (95.0 C19.365 –21.038), the treatment period (95.0 CI7.147 –20.275), during hospitalization (95.0 CI8.918 –24.237), antibiotic use (95.0 CI8.163-21.739), and hypertension (95.0 CI7.926-22.385). Using the association rule system to assay and control the major threat

免责声明: 此摘要通过人工智能工具翻译,尚未经过审核或验证。