Chen Xi, Fu Ruibiao, Shao Qian, Chen Yan, Ye Qinghuang, Li Sheng, He Xiongxiong, Zhu Jinhui
Department of General Surgery, Second Affiliated Hospital Zhejiang University School of Medicine, Hangzhou, China.
Department of Surgical Ward 1, Ningbo Women and Children's Hospital, Ningbo, China.
Front Oncol. 2022 Jul 22;12:960056. doi: 10.3389/fonc.2022.960056. eCollection 2022.
Pancreatic cancer (PC) is one of the deadliest cancers worldwide although substantial advancement has been made in its comprehensive treatment. The development of artificial intelligence (AI) technology has allowed its clinical applications to expand remarkably in recent years. Diverse methods and algorithms are employed by AI to extrapolate new data from clinical records to aid in the treatment of PC. In this review, we will summarize AI's use in several aspects of PC diagnosis and therapy, as well as its limits and potential future research avenues.
We examine the most recent research on the use of AI in PC. The articles are categorized and examined according to the medical task of their algorithm. Two search engines, PubMed and Google Scholar, were used to screen the articles.
Overall, 66 papers published in 2001 and after were selected. Of the four medical tasks (risk assessment, diagnosis, treatment, and prognosis prediction), diagnosis was the most frequently researched, and retrospective single-center studies were the most prevalent. We found that the different medical tasks and algorithms included in the reviewed studies caused the performance of their models to vary greatly. Deep learning algorithms, on the other hand, produced excellent results in all of the subdivisions studied.
AI is a promising tool for helping PC patients and may contribute to improved patient outcomes. The integration of humans and AI in clinical medicine is still in its infancy and requires the in-depth cooperation of multidisciplinary personnel.
尽管胰腺癌的综合治疗取得了显著进展，但它仍是全球最致命的癌症之一。近年来，人工智能（AI）技术的发展使其临床应用得到了显著扩展。AI采用多种方法和算法从临床记录中推断新数据，以辅助胰腺癌的治疗。在本综述中，我们将总结AI在胰腺癌诊断和治疗的几个方面的应用，以及其局限性和未来潜在的研究方向。
我们研究了关于AI在胰腺癌中应用的最新研究。根据算法的医学任务对文章进行分类和研究。使用两个搜索引擎，即PubMed和谷歌学术，来筛选文章。
总体而言，选取了2001年及以后发表的66篇论文。在四个医学任务（风险评估、诊断、治疗和预后预测）中，诊断是研究最频繁的，回顾性单中心研究最为普遍。我们发现，综述研究中包含的不同医学任务和算法导致其模型的性能差异很大。另一方面，深度学习算法在所有研究的细分领域都取得了优异的成果。
AI是帮助胰腺癌患者的一个有前途的工具，可能有助于改善患者的治疗结果。人工智能与人类在临床医学中的整合仍处于起步阶段，需要多学科人员的深入合作。
