冯晓东,史立波

乳腺癌是女性最常见的癌症之一，也是导致女性癌症相关死亡的最主要原因。早期诊断和治疗是获得良好预后的关键。人工智能（AI）技术在医学领域的应用日益广泛，包括图像分析、自动化诊断、智能制药系统、个性化治疗等，AI技术辅助的乳腺癌影像、病理技术，不仅减轻了临床医生的工作量，还不断提高乳腺癌诊疗的准确性和及时性。本文综述了AI技术在乳腺癌诊断中的应用，以期为今后的研究提供思路。

人工智能；乳腺癌；诊断；治疗

[1] Greenspan H,Ginneken BV,Summers RM(2016)Guest editorial deep learning in medical imaging:overview and future promise of an exciting new technique.IEEE Trans Med Imaging 35(5):1153-1159. [2] Rodríguez-Ruiz A,Krupinski E,Mordang JJ,Schilling K,Heywang Köbrunner SH,Sechopoulos I,Mann RM(2019)Detection of breast cancer with mammography:effect of an artificial intelligence support system.Radiology 290(2):305-314. [3] Freeman K,Geppert J,Stinton C.et al.Use of artificial intelligence for image analysis in breast cancer screening programmes:systematic review of test accuracy.BMJ 2021;374:n1872. [4] Zheng X,Yao Z,Huang Y,Yu Y,Wang Y,Liu Y,Mao R,Li F,Xiao Y,Wang Y,Hu Y,Yu J,Zhou J(2020)Deep learning radiomics can predict axillary lymph node status in early-stage breast cancer.Nat Commun 11(1):1236. [5] Shen Y,Shamout FE,Oliver JR,Witowski J et al(2021)Artificial intelligence system reduces false-positive findings in the interpretation of breast ultrasound exams.Nat Commun 12(1):5645. [6] Jun B,Russell P,Tianyu W,Clifford Y,Sheida N(2021)Applying deep learning in digital breast tomosynthesis for automatic breast cancer detection:a review.Med Image Anal 71:102049. [7] Jiang Y,Edwards AV,Newstead GM(2021)Artificial intelligence applied to breast MRI for improved diagnosis.Radiology 298(1):38-46. [8] Witowski J,Heacock L,Reig B,Kang SK,Lewin A,Pysarenko K,Patel S,Samreen N,Rudnicki W,Luczyńska E,Popiela T,Moy L,Geras KJ(2022)Improving breast cancer diagnostics with deep learning for MRI.Sci Transl Med 14(664):eabo4802. [9] Rosenstein BS,West CM,Bentzen SM et al(2014)Radiogenomics:radiobiology enters the era of big data and team science.Int J Radiat Oncol Biol Phys 89(4):709-713. [10] Litjens G,Sánchez CI,Timofeeva N et al(2016a)Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis.Sci Rep 6(1):4986. [11] Araujo T,Aresta G,Castro E et al(2017)Classification of breast cancer histology image using convolutional neural networks.PLoS One 12(6):e0177544. [12] Ortega I,Roy P et al(2020)Deep learned tissue“fingerprints”classify breast cancers by ER/PR/Her2 status from H&E images.Sci Rep 10(1):7275. [13] Xie N,Zhou H,Yu L,Huang S,Tian C,Li K,Jiang Y,Hu ZY,Ouyang Q(2022)Artificial intelligence scale-invariant feature transform algorithm-based system to improve the calculation accuracy of Ki-67 index in invasive breast cancer:a multicenter retrospective study.Ann Transl Med 10(19):1067.

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