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Coronary artery stenosis (CAS) poses a significant challenge in cardiology, requiring timely and precise diagnosis to prevent severe outcomes [1, 2]. This article explores the transformative potential of deep learning in the automated detection of CAS, focusing on methodologies, technological advancements, and clinical applications [3, 4]. Insights from the document emphasize the evolution of deep learning in medical imaging, key techniques for CAS detection, and the challenges faced in integrating these systems into clinical workflows [5, 6].

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Automated Detection of Coronary Artery Stenosis Through Deep Learning

  • 会议论文

  • 发表日期：

    2026年

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  • Hajar Rouane,
  • Salma Batahi,
  • Fatima Ezahra Mouas,
  • Kenza Belkhou,
  • Nour Akalai,
  • Achraf Benba

摘要

Coronary artery stenosis (CAS) poses a significant challenge in cardiology, requiring timely and precise diagnosis to prevent severe outcomes [1, 2]. This article explores the transformative potential of deep learning in the automated detection of CAS, focusing on methodologies, technological advancements, and clinical applications [3, 4]. Insights from the document emphasize the evolution of deep learning in medical imaging, key techniques for CAS detection, and the challenges faced in integrating these systems into clinical workflows [5, 6].