摘要
人工智能（AI）在早期胃癌内镜筛查中的应用显著提升了病变检测的准确性和效率。基于深度学习的图像识别技术能够辅助内镜医生快速定位可疑病灶，减少漏诊率，并通过自动化分析降低主观判断差异。例如，卷积神经网络（CNN）在内镜图像分类、病灶分割及恶性程度预测中展现出高敏感性和特异性，部分系统已进入临床应用阶段。然而，AI技术的推广面临多重伦理挑战如患者隐私与数据安全问题，医疗数据的采集、共享需符合严格规范；算法透明性不足导致的“黑箱”疑虑，影响医患信任；责任归属问题，AI误诊时难以界定医生、开发者及医疗机构的责任；技术普及可能加剧医疗资源分配不均等。未来需通过多学科协作制定伦理指南，确保AI在提升胃癌早诊率的同时，兼顾公平性、可解释性与临床安全性。
关键词： 人工智能；早期胃癌；内镜筛查；伦理挑战；辅助诊断
Abstract
The application of artificial intelligence (AI) in endoscopic screening for early gastric cancer has significantly improved the accuracy and efficiency of lesion detection. Image recognition technology based on deep learning can assist endoscopists in quickly locating suspicious lesions, reduce the rate of missed diagnosis, and reduce subjective judgment differences through automated analysis. For example, convolutional neural networks (CNNs) have shown high sensitivity and specificity in endoscopic image classification, lesion segmentation, and malignancy prediction, and some systems have entered the clinical application stage. However, the promotion of AI technology faces multiple ethical challenges, such as patient privacy and data security issues. The collection and sharing of medical data must comply with strict regulations; the "black box" concerns caused by the lack of algorithm transparency affect the trust between doctors and patients; the issue of responsibility attribution. It is difficult to define the responsibilities of doctors, developers, and medical institutions when AI misdiagnoses; the popularization of technology may aggravate the unequal distribution of medical resources. In the future, it is necessary to formulate ethical guidelines through multidisciplinary collaboration to ensure that AI can improve the early diagnosis rate of gastric cancer while taking into account fairness, explainability, and clinical safety.
Key words： Artificial intelligence; Early gastric cancer; Endoscopic screening; Ethical challenges; Auxiliary diagnosis
参考文献 References
[1] Xiao, Zili, et al. "Application of artificial intelligence in early gastric cancer diagnosis." Digestion 103.1 (2022): 69-75.
[2] Chen, Pei-Chin, et al. "The accuracy of artificial intelligence in the endoscopic diagnosis of early gastric cancer: pooled analysis study." Journal of medical Internet research 24.5 (2022): e27694.
[3] Wang, Zhe, Yang Liu, and Xing Niu. "Application of artificial intelligence for improving early detection and prediction of therapeutic outcomes for gastric cancer in the era of precision oncology." Seminars in Cancer Biology. Vol. 93. Academic Press, 2023.
[4] Anta, Julia Arribas, and Mario Dinis-Ribeiro. "Early gastric cancer and Artificial Intelligence: Is it time for population screening?." Best Practice & Research Clinical Gastroenterology 52 (2021): 101710.
[5] Wu, Lianlian, et al. "Evaluation of the effects of an artificial intelligence system on endoscopy quality and preliminary testing of its performance in detecting early gastric cancer: a randomized controlled trial." Endoscopy 53.12 (2021): 1199-1207.
[6] Goto, Atsushi, et al. "Cooperation between artificial intelligence and endoscopists for diagnosing invasion depth of early gastric cancer." Gastric Cancer 26.1 (2023): 116-122.
[7] Ishioka, Mitsuaki, et al. "Performance of an artificial intelligence‐based diagnostic support tool for early gastric cancers: Retrospective study." Digestive Endoscopy 35.4 (2023): 483-491.
[8] Jiang, Kailin, et al. "Current evidence and future perspective of accuracy of artificial intelligence application for early gastric cancer diagnosis with endoscopy: a systematic and meta-analysis." Frontiers in Medicine 8 (2021): 629080.
[9] 黄丽,吴练练,朱益洁,等.人工智能胃镜检查辅助系统用于早期胃癌筛查的成本和效益分析[J].中华消化内镜杂志, 2023, 40(12):1001-1005.
[10] 沈耀,占强,安方梅.人工智能辅助内镜在胃癌前病变及早期胃癌诊断中的应用进展[J].中华消化内镜杂志, 2024, 41(07):582-585.
[11] 吴宏博,姚幸雨,曾丽莎,et al.基于卷积神经网络的人工智能技术在早期胃癌识别中的应用[J].第三军医大学学报, 2021, 43(18):8.
[12] 孙红霞.人工智能辅助放大内镜检查对早期胃癌检出率的影响[J].中文科技期刊数据库（文摘版）医药卫生, 2024(002):000.
[13] 方圆,郑杨,黄陈.人工智能技术在胃肠肿瘤临床诊断及外科治疗中的应用[J].中华解剖与临床杂志, 2025, 30 (01): 65-72.
[14] 苏德健.面向共聚焦激光显微内镜数据的早期胃癌智能辅助诊断方法研究[D].山东师范大学,2024.
[15] 刘 洋,胡奕炀,刘月平,et al.人工智能辅助技术在胃癌新辅助化疗患者 HER2表达评估中的价值[J].China Oncology, 2023, 33(4).
[16] 唐德华.人工智能在早期胃癌检出及性质判断中的临床研究[D].南京大学,2021.