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Artificial Intelligence for Breast Ultrasound: Will It Impact Radiologists' Accuracy?

作者信息

Bahl Manisha

机构信息

Massachusetts General Hospital, Department of Radiology, Boston, MA, USA.

出版信息

J Breast Imaging. 2021 Apr 26;3(3):312-314. doi: 10.1093/jbi/wbab022. eCollection 2021 May-Jun.

DOI:10.1093/jbi/wbab022
PMID:34056592
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8139610/
Abstract
摘要

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Screening Breast Ultrasound Using Handheld or Automated Technique in Women with Dense Breasts.在乳腺致密的女性中使用手持或自动技术进行乳腺超声筛查。
J Breast Imaging. 2019 Dec 5;1(4):283-296. doi: 10.1093/jbi/wbz055.
2
Impact of Original and Artificially Improved Artificial Intelligence-based Computer-aided Diagnosis on Breast US Interpretation.基于人工智能的原始及人工改进的计算机辅助诊断对乳腺超声解读的影响
J Breast Imaging. 2021 May 21;3(3):301-311. doi: 10.1093/jbi/wbab013.
3
Using Time as a Measure of Impact for AI Systems: Implications in Breast Screening.将时间用作人工智能系统影响的衡量标准：对乳腺筛查的启示。
Radiol Artif Intell. 2019 Jul 31;1(4):e190107. doi: 10.1148/ryai.2019190107. eCollection 2019 Jul.
4
Deep learning-based computer-aided diagnosis in screening breast ultrasound to reduce false-positive diagnoses.基于深度学习的计算机辅助诊断在乳腺超声筛查中减少假阳性诊断。
Sci Rep. 2021 Jan 11;11(1):395. doi: 10.1038/s41598-020-79880-0.
5
One step further into the blackbox: a pilot study of how to build more confidence around an AI-based decision system of breast nodule assessment in 2D ultrasound.更进一步走进黑箱：一个试点研究，探讨如何在二维超声中建立基于人工智能的乳腺结节评估决策系统的信心。
Eur Radiol. 2021 Jul;31(7):4991-5000. doi: 10.1007/s00330-020-07561-7. Epub 2021 Jan 6.
6
Can an Artificial Intelligence Decision Aid Decrease False-Positive Breast Biopsies?人工智能决策辅助工具能否减少乳腺活检的假阳性结果？
Ultrasound Q. 2020 Dec 28;37(1):10-15. doi: 10.1097/RUQ.0000000000000550.
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Artificial Intelligence: A Primer for Breast Imaging Radiologists.人工智能：乳腺影像放射科医生入门指南。
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AJR Am J Roentgenol. 2020 Jun;214(6):1424-1435. doi: 10.2214/AJR.19.22275. Epub 2020 Mar 17.
10
Artificial Intelligence for Mammography and Digital Breast Tomosynthesis: Current Concepts and Future Perspectives.人工智能在乳腺 X 线摄影和数字乳腺断层合成中的应用：现状与未来展望。
Radiology. 2019 Nov;293(2):246-259. doi: 10.1148/radiol.2019182627. Epub 2019 Sep 24.