［1］马丹丹，刘坤，齐晓伟.2018年全球癌症统计：乳腺癌发病和死亡人数统计［J］.中华乳腺病杂志(电子版)，2018，12(06)：375.
MA DD，LIU K，QI XW.Global cancer statistics 2018：Incidence rate and mortality statistics of breast cancer［J］.Chinese Journal of Breast Disease(Electronic Edition)，2018，12(06)：375.
［2］WANG F，YU ZG.Current status of breast cancer prevention in China［J］.Chronic Diseases and Translational Medicine，2015，1(1)：2-8.
［3］姚云清.新技术革命对现代医学发展的影响［J］.西北医学教育，2004，12(S1)：1-3.
YAO YQ.The influence of new technology revolution on the development of modern medicine［J］.Northwest Medical Education，2004，12(S1)：1-3.
［4］CHEN W，ZHENG R，BAADE PD，et al.Cancer statistics in China，2015［J］.CA Cancer J Clin，2016，66(2)：115-132.
［5］FAN L，ZHENG Y，YU KD，et al.Breast cancer in a transitional society over 18 years：Trends and present status in Shanghai，China［J］.Breast Cancer Res Treat，2009，117(2)：409-416.
［6］GAO YT，SHU XO，DAI Q，et al.Association of menstrual and reproductive factors with breast cancer risk：Results from the Shanghai breast cancer study［J］.Int J Cancer，2000，87(2)：295-300.
［7］HOLMES JH，SACCHI L，BELLAZZI R，et al.Artificial intelligence in medicine AIME 2015［J］.Artificial Intelligence in Medicine，2017，81：1-2.
［8］GINNEKEN B.Fifty years of computer analysis in chest imaging：Rule-based，machine learning，deep learning［J］.Radiol Phys Technol，2017，10(1)：23-32.
［9］MENDELSON EB.Artificial intelligence in breast imaging：Potentials and limitations［J］.Am J Roentgenol，2019,212(2)：293-299.
［10］罗凤，陈金鹰，李果村.人工智能技术在医学领域的应用分析［J］.通信与信息技术，2018，236(06)：27-28.
LUO F，CHEN JY，LI GC.Analysis of the application of artificial intelligence technology in the field of medicine［J］.Communication and Information Technology，2018，236(06)：27-28.
［11］HINTON GE，OSINDERO S，TEH YW.A fast learning algorithm for deep belief nets［J］.Neural computation，2006，18(7)：1527-1554.
［12］IVAKHNENKO AG.Polynomial theory of complex systems:IEEE trans syst man cybern［J］.IEEE Transactions on Systems Man and Cybernetics，1971，1(4)：364-378.
［13］COLE EB，ZHANG Z，MARQUES HS，et al.Impact of computer-aided detection systems on radiologist accuracy with digital mammography［J］.Am J Roentgenol，2014，203(4)：909-916.
［14］KOOI T，LITJENS G，VAN GINNEKEN B，et al.Large scale deep learning for computer aided detection of mammographic lesions［J］.Medical Image Analysis，2017，35：303-312.
［15］FAZAL MI，PATEL ME，TYE J，et al.The past，present and future role of artificial intelligence in imaging［J］.Eur J Radiol，2018，105：246-250.
［16］LIBERMAN L，ABRAMSON AF，SQUIRES FB，et al.The breast imaging reporting and data system：positive predictive value of mammographic features and final assessment categories［J］.Am J Roentgenol，1998，171(1)：35-40.
［17］SAMALA RK，CHAN HP，HADJIISKI LM，et al.Multi-task transfer learning deep convolutional neural network：Application to computer-aided diagnosis of breast cancer on mammograms［J］.Phys Med Biol，2017，62(23)：8894-8908.
［18］WANG J，YANG X，CAI H，et al.Discrimination of breast cancer with microcalcifications on mammography by deep learning［J］.Scientific Reports，2016，6(5)：1-4.
［19］ORTIZ-RODRIGUEZ JM，GUERRERO-MENDEZ C，MARTINEZ-BLANCO MDR，et al.Breast cancer detection by means of artificial neural networks［J］.Advanced Applications for Artificial Neural Networks，2018(1)：161-176.
［20］MOHAMED AA，BERG WA，PENG H，et al.A deep learning method for classifying mammographic breast density categories［J］.Med Phys，2018，45(1)：314-321.
［21］RODRíGUEZ-RUIZ A，KRUPINSKI E，MORDANG JJ，et al.Detection of breast cancer with mammography：Effect of an artificial intelligence support system［J］.Radiology，2019，290(2)：305-314.
［22］QI X，ZHANG L，CHEN Y，et al.Automated diagnosis of breast ultrasonography images using deep neural networks［J］.Medical Image Analysis，2019，52：185-198.
［23］HAN S，KANG HK，JEONG JY，et al.A deep learning framework for supporting the classification of breast lesions in ultrasound images［J］.Phys Med Biol，2017，62(19)：7714-7728.
［24］CHIANG TC，HUANG YS，CHEN RT，et al.Tumor detection in automated breast ultrasound using 3-D CNN and prioritized candidate aggregation［J］.IEEE Trans Med Imaging，2019，38(1)：240-249.
［25］ZHOU J，LUO L，DOU Q，et al.Weakly supervised 3D deep learning for breast cancer classification and localization of the lesions in MR images［J］.Journal of Magnetic Resonance Imaging，2019，50(4)：1144-1151.
［26］GALLEGO-ORTIZ C，MARTEL AL.A graph-based lesion characterization and deep embedding approach for improved computer-aided diagnosis of nonmass breast MRI lesions［J］.Medical Image Analysis，2019，51：116-124.
［27］HA R，MUTASA S，KARCICH J，et al.Predicting breast cancer molecular subtype with MRI dataset utilizing convolutional neural network algorithm［J］.Journal of Digital Imaging，2019，32(2)：276-282.
［28］HERENT P，SCHMAUCH B，JEHANNO P，et al.Detection and characterization of MRI breast lesions using deep learning［J］.Diagn Interv Imaging，2019，100(4)：219-225.
［29］HA R，CHIN C，KARCICH J，et al.Prior to initiation of chemotherapy，can we predict breast tumor response:Deep learning convolutional neural networks approach using a breast MRI tumor dataset［J］.Journal of Digital Imaging，2019，32(5)：693-701.
［30］IBRAHIM A，GAMBLE P，JAROENSRI R，et al.Artificial intelligence in digital breast pathology：Techniques and applications［J］.The Breast，2020,49：267-273.
［31］LITJENS G，SáNCHEZ CI，TIMOFEEVA N，et al.Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis［J］.Scientific Reports，2016，6(1):4986.
［32］EHTESHAMI BB，VETA M，JOHANNES VDP，et al.Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer［J］.JAMA，2017，318(22)：2199-2210.
［33］ZADEH SA，SEYYED MCSJ，MOHAMMADI Z.A novel and reliable computational intelligence system for breast cancer detection［J］.Med Biol Eng Comput，2018，56(5)：721-732.
［34］ARAUJO T，ARESTA G，CASTRO E，et al.Classification of breast cancer histology image using Convolutional Neural Networks［J］.PLoS One，2017，12(6)：e0177544.
［35］CABALLO M，PANGALLO DR，MANN RM，et al.Deep learning-based segmentation of breast masses in dedicated breast CT imaging：Radiomic feature stability between radiologists and artificial intelligence［J］.Computers in Biology and Medicine，2020，118：103629.
［36］于观贞，魏培莲，陈颖，等.人工智能在肿瘤病理诊断和评估中的应用与思考［J］.第二军医大学学报，2017，38(11)：1349-1354.
YU GZ，WEI PL，CHEN Y，et al.Application and thinking of artificial intelligence in tumor pathological diagnosis and evaluation［J］.Journal of the Second Military Medical University，2017，38(11)：1349-1354.
［37］科学家使用人工智能改善早期乳腺癌诊断［J］.健康管理，2017，11(10)：9-10.
Scientists use artificial intelligence to improve the diagnosis of early breast cancer［J］.Health Management，2017，11(10)：9-10.
［38］MARIO C.Deep learning technology for improving cancer care in society：New directions in cancer imaging driven by artificial intelligence［J］.Technology in Society，2020，60：101198.
［39］SECHOPOULOS I，MANN RM.Stand-alone artificial intelligence:The future of breast cancer screening［J］.The Breast，2020，49：254-260.