中国全科医学 ›› 2022, Vol. 25 ›› Issue (18): 2215-2222.DOI: 10.12114/j.issn.1007-9572.2022.0095

• 论著·宫颈癌专题研究 • 上一篇    下一篇

人工智能在宫颈病变诊断及治疗中的应用进展与挑战

武爱媛1, 热米拉·热扎克1,*(), 乔友林1,2   

  1. 1.830011 新疆维吾尔自治区乌鲁木齐市,新疆医科大学附属肿瘤医院 省部共建中亚高发病成因与防治国家重点实验室
    2.100730 北京市,中国医学科学院北京协和医学院群医学及公共卫生学院
  • 收稿日期:2022-01-25 修回日期:2022-03-01 出版日期:2022-06-20 发布日期:2022-04-20
  • 通讯作者: 热米拉·热扎克
  • 武爱媛,热米拉·热扎克,乔友林.人工智能在宫颈病变诊断及治疗中的应用进展与挑战[J].中国全科医学,2022,25(18):2215-2222,2230. [www.chinagp.net]
    作者贡献:武爱媛进行文章的构思与设计,提出主要分析指标,负责检索文献、撰写论文;热米拉·热扎克进行论文的修订、质量控制及审校;乔友林对文章整体负责,监督管理。
  • 基金资助:
    省部共建中亚高发病成因与防治国家重点实验室开放课题资助项目(SKL-HIDCA-2020-GJ2); 新疆医科大学研究生创新创业项目

Progress and Challenge of Artificial Intelligence in Diagnosis and Treatment of Cervical Lesions

Aiyuan WU1, ·Rezhake REMILA1,*(), Youlin QIAO1,2   

  1. 1. Affiliated Tumor Hospital of Xinjiang Medical University/State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Urumqi 830011, China
    2. School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
  • Received:2022-01-25 Revised:2022-03-01 Published:2022-06-20 Online:2022-04-20
  • Contact: ·Rezhake REMILA
  • About author:
    WU A Y, REMILA R, QIAO Y L. Progressand challenge of artificial intelligencein diagnosis and treatment of cervical lesions[J]. Chinese General Practice, 2022, 25 (18) : 2215-2222, 2230.

摘要: 我国宫颈癌的疾病负担较重,其发病率和死亡率呈逐年升高且年轻化趋势,防控形势较为严峻,急需探索适宜我国不同资源地区的、新型的早诊早治手段,以加快我国宫颈癌的防治步伐。近些年人工智能(AI)在图像分类领域取得较大进展,科学家们开发出众多能够识别宫颈病变的算法,并对其准确性进行了相应的研究。本文结合国内外研究成果,就AI在宫颈细胞学筛查、阴道镜、宫颈恶性肿瘤的诊断及治疗预测过程等方面的应用进展进行综述,并探讨AI在宫颈病变诊断及治疗中遇到的挑战,使AI协助医疗工作者更好地为人类健康保驾护航。

关键词: 宫颈疾病, 人工智能, 细胞学技术, 宫颈细胞学, 阴道镜检查, 筛查, 诊断, 鉴别, 治疗

Abstract:

China has the considerable disease burden of cervical cancer, with the mortality and morbidity of cervical cancer showing an increasing and younger trend. Facing to the critical situation of cervical cancer control, it is urgent to explore the new methods that suitable for different resource areas for the early detection and treatment of cervical cancer. Recently, great progress has been made in the field of AI image classification, and scientists have developed many algorithms to identify cervical lesions and conducted corresponding studies on their accuracy. Here, by reviewing the papers published at home and aboard, which studied the applications value of AI in cervical cytology screening, colposcopy examination, diagnosis and treatment of cervical cancer, we summarized and discussed the current progress and challenges for AI's application in the area of cervical cancer control, in order to provide solid evidence for the future use of AI in improving human health.

Key words: Uterine cervical diseases, Artificial intelligence, Cytological techniques, Cervical cytology, Colposcopy, Screening, Diagnosis, differential, Treatment