山东大学耳鼻喉眼学报 ›› 2023, Vol. 37 ›› Issue (2): 135-142.doi: 10.6040/j.issn.1673-3770.0.2022.089

• 综述 • 上一篇    下一篇

人工智能在鼻咽癌诊断与治疗中的应用研究进展

刘佳钰,樊慧明,邹游,陈始明   

  1. 武汉大学人民医院 耳鼻咽喉头颈外科, 湖北 武汉 430060
  • 发布日期:2023-03-30
  • 通讯作者: 陈始明. E-mail:shmingchen0468@163.com
  • 基金资助:
    国家自然科学基金(82002863)

Research progress on the application of artificial intelligence in the diagnosis and treatment of nasopharyngeal carcinoma

LIU Jiayu, FAN Huiming, ZOU You, CHEN Shiming   

  1. Department of Otorhinolaryngology & Head and Neck Surgery, Renmin Hospital of Wuhan University, Wuhan 430060, Hubei, China
  • Published:2023-03-30

摘要: 鼻咽癌在我国华南地区高发,由于传统诊疗方式受到各种主观因素和客观因素的影响,且效率低下,因此探寻更为客观、稳定、高效的诊疗手段迫在眉睫。近年来,人工智能广泛应用于肿瘤的诊断和治疗当中,在图像识别、分割、风险预测及疗效预测等方面均显示出较高的准确性。此外,应用人工智能模型辅助临床医师诊疗工作可大大缩减所需时间、提高临床医师诊疗准确性并减小医师之间观察者变异度,为更好地诊治肿瘤创造了条件。论文就人工智能在鼻咽癌诊疗方面的应用现状及价值进行综述与总结,并对其未来发展方向进行展望。

关键词: 鼻咽癌, 人工智能, 机器学习, 深度学习, 卷积神经网络, 支持向量机

Abstract: The incidence of nasopharyngeal carcinoma is high in southern China. As traditional diagnosis and treatment methods are affected by both low efficiency and subjective and objective factors, a more objective, stable and efficient method of diagnosis and treatment is urgently needed. Artificial intelligence has been widely used in tumor diagnosis and treatment, and has shown high accuracy in image recognition, segmentation, risk prediction, and efficacy prediction. In addition, the application of AI models to assist clinicians in diagnosis and treatment can significantly reduce the amount of time required, improve the accuracy of clinicians' performance, and reduce observer variability among physicians, establishing conditions for enhanced tumor diagnosis and treatment. In this paper, the application status and value of artificial intelligence in the diagnosis and treatment of nasopharyngeal carcinoma are reviewed and summarized, and its future development direction is discussed.

Key words: Nasopharyngeal carcinoma, Artificial intelligence, Machine learning, Deep learning, Convolutional neural network, Support vector machine

中图分类号: 

  • R766.3
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