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Will Machine Learning Tip the Balance in Breast Cancer Screening?
JAMA Oncol. 2017 Nov 1;3(11):1463-1464. doi: 10.1001/jamaoncol.2017.0473.
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3
Digital Mammography and Digital Breast Tomosynthesis.
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Tomosynthesis in Breast Cancer Imaging: How Does It Fit into Preoperative Evaluation and Surveillance?
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Automated Breast Cancer Diagnosis Based on Machine Learning Algorithms.
J Healthc Eng. 2019 Nov 3;2019:4253641. doi: 10.1155/2019/4253641. eCollection 2019.
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Digital mammography: clinical image evaluation.
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The basics and implementation of digital mammography.
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Comparison of handheld ultrasound and automated breast ultrasound in women recalled after mammography screening.
Acta Radiol. 2017 May;58(5):515-520. doi: 10.1177/0284185116665421. Epub 2016 Sep 30.

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An Introduction to Machine Learning for Speech-Language Pathologists: Concepts, Terminology, and Emerging Applications.
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Investigating awareness of artificial intelligence in healthcare among medical students and professionals in Pakistan: a cross-sectional study.
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Use of artificial intelligence in breast surgery: a narrative review.
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A divide and conquer approach to maximise deep learning mammography classification accuracies.
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Signals of global symmetry are important for abnormality detection in mammograms.
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本文引用的文献

1
Breast-Cancer Tumor Size, Overdiagnosis, and Mammography Screening Effectiveness.
N Engl J Med. 2016 Oct 13;375(15):1438-1447. doi: 10.1056/NEJMoa1600249.
2
Predicting the Future - Big Data, Machine Learning, and Clinical Medicine.
N Engl J Med. 2016 Sep 29;375(13):1216-9. doi: 10.1056/NEJMp1606181.
3
Large scale deep learning for computer aided detection of mammographic lesions.
Med Image Anal. 2017 Jan;35:303-312. doi: 10.1016/j.media.2016.07.007. Epub 2016 Aug 2.
4
Machine Learning and the Profession of Medicine.
JAMA. 2016 Feb 9;315(6):551-2. doi: 10.1001/jama.2015.18421.
5
Machine Learning in Medicine.
Circulation. 2015 Nov 17;132(20):1920-30. doi: 10.1161/CIRCULATIONAHA.115.001593.
6
Diagnostic Accuracy of Digital Screening Mammography With and Without Computer-Aided Detection.
JAMA Intern Med. 2015 Nov;175(11):1828-37. doi: 10.1001/jamainternmed.2015.5231.
7
Systematic analysis of breast cancer morphology uncovers stromal features associated with survival.
Sci Transl Med. 2011 Nov 9;3(108):108ra113. doi: 10.1126/scitranslmed.3002564.

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