Repository logo
  • English
  • 中文
  • Log In
    New user? Click here to register.Have you forgotten your password?
Repository logo
    Communities & Collections
    Research Outputs
    Fundings & Projects
    People
    Organizations
    Statistics
  • English
  • 中文
  • Log In
    New user? Click here to register.Have you forgotten your password?
  1. Home
  2. .TMU Publications / 北醫出版品(教師升等著作 / 教學實踐 / 學位論文)
  3. .博碩士學位論文
  4. 111學年度
  5. 論 AI 影像輔助診斷產品對急診室醫療品質管理之提升
 
  • Details
Options

論 AI 影像輔助診斷產品對急診室醫療品質管理之提升

Other Title
Using Image AI Software to Improve and Optimize the Efficiency of ICH's Clinical Process in Emergency Room Operations
Type
thesis
Date Issued
2022-12-28
Author(s)
陳彥諭
Advisor
李友專
Subjects
系所名稱:醫學資訊研究所碩士在職專班
Description
學位別:碩士
語文別:英文
口試委員:張文信 CHANG, WEN-HSIN;林哲瑋 CHE-WEI LIN;李友專 LI, YU-CHUAN
授權範圍:網際網路,開放日期為2023-01-13
Abstract
在急診室中治療出血性中風是與時間賽跑的過程。提高決策的準確性和執行醫囑的速度將有助於更及時地治療病患,從而提高治療品質和恢復情況。

近年來,臨床決策支持系統(CDSS)結合人工智慧(AI)於醫療領域的應用越來越多,本研究證明,CDSS和醫生之間的關係不是競爭或相互排斥。

本研究有兩個主要目標。 第一,驗證在獲得疑似腦內出血(ICH)患者的CT掃描圖像后,立即利用AI自動輔助解讀,是否能降低臨床誤診率。 第二,在急診科(ED)的真實環境中測試和導入這種人工智慧工具,並驗證其在優化臨床工作流程方面的真實表現。

這項臨床試驗研究的假設是,帶有深度學習(DL)的無顯影電腦斷層掃描(NCCT)可協助檢測ICH,從而加快急診科的臨床效率,減少病患於急診科的停留時間(LOS)。

本研究共納入了2,999名患者(最終診斷為ICH和無ICH的患者分別為188名和2,811名)。我們的研究旨在驗證使用人工智慧軟體工具DeepCT是否能縮短ICH患者在急診科的停留時間。

臨床結果顯示,在急診室導入DeepCT系統後,最終診斷為ICH的患者的LOS明顯縮短(使用DeepCT的 560.67±124.12分鐘與不使用DeepCT的780.83±147.35分鐘; P = 0.0251)。
URI
https://handle.ncl.edu.tw/11296/9rj27j
https://203.71.86.71/handle/123456789/10061

Copyright Notice

● The digital content on this platform is part of the Taipei Medical University Institutional Repository, featuring various academic works and outputs from the institution. It offers free access to academic research and public education for non-commercial use.

● Please use the content appropriately and within legal boundaries to respect copyright owners' rights. For commercial use, please obtain prior authorization from the copyright owner. Users must not use TMUIR for any illegal purposes.

● By utilising the platform, users are deemed to have fully accepted and understood all the regulations set out in this statement, relevant laws of the Republic of China, all international internet regulations, and usage conventions.

● TMUIR is committed to protecting the interests of copyright owners. If you believe that any material on this website infringes copyright, please contact our staff at libirtmu@gmail.com, and we will remove the work from the repository.

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science

  • Cookie settings
  • Privacy policy
  • End User Agreement
  • Send Feedback