机器学习在乳腺癌全程全方位管理中的研究进展  

Research Progress of Machine Learning in Omni-directional Management of Breast Cancer

作　　者：徐一云 陈佳静 秦悦农[1] 吴春宇[1] 孙霃平[1] 刘胜[1] XU Yiyun;CHEN Jiajing;QIN Yuenong;WU Chunyu;SUN Chenping;LIU Sheng(Department of Integrated Chinese and Western Medicine for Breast Diseases,Longhua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine,Shanghai 200032,China)

机构地区：[1]上海中医药大学附属龙华医院中西医结合乳腺科,上海200032

出　　处：《医学综述》2021年第22期4465-4469,共5页Medical Recapitulate

基　　金：上海市卫生计生委智慧医疗专项研究项目(2018ZHYL0206);上海中医药大学附属龙华医院国家中医临床研究基地龙医学者(育苗计划)(LYTD-79);促进市级医院临床技能与临床创新三年行动计划(SHDC2020CR1050B)。

摘　　要：乳腺恶性肿瘤已成为现代女性发病率最高的恶性肿瘤。伴随乳腺癌确诊患者的增加,其相关影像、病理、检验报告、治疗方案的诊疗数据也急剧增长。然而随着医师工作强度的增加,也面临误诊率、漏诊率升高等问题。机器学习可通过海量数据变量揭示数据特征之间的关系、预测事件结局并提供可能的决策,因此广泛应用于乳腺恶性肿瘤的中西医诊疗、并发症的早期识别、肿瘤相关心理干预、风险预测等方面,具有良好的临床应用前景。未来基于机器学习的数字化医疗可以为乳腺癌的传统诊治流程及疾病全方位管理模式提供新思路。Breast cancer has become the malignant tumor of the highest incidence in modern women.Along with the increase of patients diagnosed with breast cancer,the diagnosis and treatment data of imaging,pathology,test report and treatment plan also increased sharply.However,with the increase of work intensity of the physicians,the problems such as the increase of misdiagnosis rate and missed diagnosis rate also occur.Machine learning can reveal the relationship between data features,predict event outcomes and provide possible decisions through massive data variables.Therefore,machine learning has been widely used in the diagnosis and treatment of breast cancer with traditional Chinese medicine and western medicine,early identification of complications,tumor-related psychological intervention,risk prediction and other aspects,and has a good clinical application prospect.In the future,digital medical treatment based on machine learning can provide new ideas for the traditional diagnosis and treatment process of breast cancer and the comprehensive management model of the disease.

关 键 词：乳腺癌 机器学习 中西医结合 中医客观化 

分 类 号：R737.9[医药卫生—肿瘤]