Ready for testing artificial intelligence in radiology clinical practice: We would do well to be in the front line leveraging their strengths but also highlighting today weaknesses.
作者信息
Bender Benjamin
机构信息
Department of Diagnostic and Interventional Neuroradiology, Radiologic Clinics, University Hospital Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany.
出版信息
Eur Radiol. 2024 Feb;34(2):808-809. doi: 10.1007/s00330-023-10240-y. Epub 2023 Sep 22.
Abstract
摘要
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Ready for testing artificial intelligence in radiology clinical practice: We would do well to be in the front line leveraging their strengths but also highlighting today weaknesses.准备好在放射学临床实践中测试人工智能：我们最好站在前沿，利用其优势，但也要指出其目前的弱点。
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本文引用的文献
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Effects of a comprehensive brain computed tomography deep learning model on radiologist detection accuracy.基于深度学习的脑 CT 综合模型对放射科医生检测准确率的影响。
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Artificial Intelligence for Image Interpretation: Point-The Radiologist's Potential Friend.用于图像解读的人工智能：关键——放射科医生潜在的帮手。
AJR Am J Roentgenol. 2021 Sep;217(3):556-557. doi: 10.2214/AJR.21.25564. Epub 2021 Feb 3.
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Artificial Intelligence for Image Interpretation: Counterpoint-The Radiologist's Incremental Foe.用于图像解读的人工智能：反驳观点——放射科医生日益增加的对手
AJR Am J Roentgenol. 2021 Sep;217(3):558-559. doi: 10.2214/AJR.21.25484. Epub 2021 Feb 3.
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Artificial intelligence in medical imaging: switching from radiographic pathological data to clinically meaningful endpoints.人工智能在医学影像学中的应用：从放射病理数据到临床有意义的终点的转变。
Lancet Digit Health. 2020 Sep;2(9):e486-e488. doi: 10.1016/S2589-7500(20)30160-6.
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Speed Versus Interpretation Accuracy: Current Thoughts and Literature Review.速度与解释准确性：当前的思考与文献综述。
AJR Am J Roentgenol. 2019 Sep;213(3):490-492. doi: 10.2214/AJR.19.21290. Epub 2019 Jun 5.
6
Accuracy of preliminary interpretation of neurologic CT examinations by on-call radiology residents and assessment of patient outcomes at a level I trauma center.一级创伤中心值班放射科住院医师对神经 CT 检查初步解读的准确性及其对患者预后的评估。
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