Artificial Intelligence in Breast Imaging: Potentials and Limitations

被引：75

作者：

Mendelson, Ellen B. ^{[1
]}

机构：

[1] Northwestern Univ, Prentice Hosp Northwestern Mem, Lynn Sage Breast Imaging Ctr, Feinberg Sch Med, Suite 4-2304,250 Super St, Chicago, IL 60611 USA

来源：

AMERICAN JOURNAL OF ROENTGENOLOGY | 2019年 / 212卷 / 02期

关键词：

artificial intelligence in breast imaging; artificial intelligence in radiology; artificial neural networks; computer-aided detection and diagnosis; machine and deep learning; COMPUTER-AIDED DIAGNOSIS; LYMPH-NODE STATUS; NEURAL-NETWORKS; BI-RADS; HEALTH-CARE; RADIOLOGY; CANCER; PREDICTION; FUTURE; CLASSIFICATION;

D O I：

10.2214/AJR.18.20532

中图分类号：

R8 [特种医学]; R445 [影像诊断学];

学科分类号：

1002 ; 100207 ; 1009 ;

摘要：

OBJECTIVE. The purpose of this article is to discuss potential applications of artificial intelligence (AI) in breast imaging and limitations that may slow or prevent its adoption. CONCLUSION. The algorithms of AI for workflow improvement and outcome analyses are advancing. Using imaging data of high quality and quantity, AI can support breast imagers in diagnosis and patient management, but AI cannot yet be relied on or be responsible for physicians' decisions that may affect survival. Education in AI is urgently needed for physicians.

引用

页码：293 / 299

页数：7

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