Stomach cancer has a high annual mortality rate worldwide necessitating early detection and accurate treatment. Even experienced specialists can make erroneous judgments based on several factors. Artificial intelligence (AI) technologies are being developed rapidly to assist in this field. Here, we aimed to determine how AI technology is used in gastric cancer diagnosis and analyze how it helps patients and surgeons. Early detection and correct treatment of early gastric cancer (EGC) can greatly increase survival rates. To determine this, it is important to accurately determine the diagnosis and depth of the lesion and the presence or absence of metastasis to the lymph nodes, and suggest an appropriate treatment method. The deep learning algorithm, which has learned gastric lesion endoscopyimages, morphological characteristics, and patient clinical information, detects gastric lesions with high accuracy, sensitivity, and specificity, and predicts morphological characteristics. Through this, AI assists the judgment of specialists to help select the correct treatment method among endoscopic procedures and radical resections and helps to predict the resection margins of lesions. Additionally, AI technology has increased the diagnostic rate of both relatively inexperienced and skilled endoscopic diagnosticians. However, there were limitations in the data used for learning, such as the amount of quantitatively insufficient data, retrospective study design, single-center design, and cases of non-various lesions. Nevertheless, this assisted endoscopic diagnosis technology that incorporates deep learning technology is sufficiently practical and future-oriented and can play an important role in suggesting accurate treatment plans to surgeons for resection of lesions in the treatment of EGC.

中文翻译：

---

人工智能在胃癌中的作用：手术和治疗的观点：综合回顾。

胃癌在全球范围内的年死亡率很高，需要早期发现和准确治疗。即使是经验丰富的专家也可能根据多种因素做出错误的判断。人工智能 (AI) 技术正在迅速发展，以协助这一领域。在这里，我们的目的是确定人工智能技术如何用于胃癌诊断，并分析它如何帮助患者和外科医生。早期胃癌（EGC）的早期发现和正确治疗可以大大提高生存率。为了确定这一点，重要的是准确确定病变的诊断和深度以及是否存在淋巴结转移，并建议适当的治疗方法。深度学习算法学习了胃病变内窥镜图像、形态特征和患者临床信息，以高精度、敏感性和特异性检测胃病变并预测形态特征。通过AI辅助专家的判断，帮助在内镜手术和根治性切除中选择正确的治疗方法，并帮助预测病灶的切除边缘。此外，人工智能技术还提高了相对缺乏经验和技术熟练的内窥镜诊断医生的诊断率。但用于学习的数据存在定量不足、回顾性研究设计、单中心设计、病例非多种病变等局限性。尽管如此，这种结合深度学习技术的辅助内镜诊断技术具有足够的实用性和面向未来的能力，可以在EGC治疗中为外科医生提出准确的病灶切除治疗方案建议发挥重要作用。