Letter to the Editor regarding study design for diagnostic performance of S-detect in differentiating breast masses.
作者信息
Naidu Jatin Sridhar, Muthyala Hitesh
机构信息
Division of Surgery and Interventional Sciences, University College London, London, United Kingdom.
UCL Medical School, Faculty of Medical Sciences,, University College London, London, United Kingdom.
出版信息
Br J Radiol. 2025 Aug 1;98(1172):1333. doi: 10.1093/bjr/tqaf109.
Abstract
摘要
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本文引用的文献
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Diagnostic performance of ultrasound with computer-aided diagnostic system in detecting breast cancer.超声联合计算机辅助诊断系统检测乳腺癌的诊断性能
Heliyon. 2023 Oct 6;9(10):e20712. doi: 10.1016/j.heliyon.2023.e20712. eCollection 2023 Oct.
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Deep Learning-Based Computer-Aided Diagnosis for Breast Lesion Classification on Ultrasound: A Prospective Multicenter Study of Radiologists Without Breast Ultrasound Expertise.基于深度学习的超声乳腺病变计算机辅助诊断：无乳腺超声专业知识的放射科医师的前瞻性多中心研究。
AJR Am J Roentgenol. 2023 Oct;221(4):450-459. doi: 10.2214/AJR.23.29328. Epub 2023 May 24.
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The diagnostic performance of ultrasound computer-aided diagnosis system for distinguishing breast masses: a prospective multicenter study.超声计算机辅助诊断系统鉴别乳腺肿块的诊断性能：一项前瞻性多中心研究。
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