人工智能在消化系统肿瘤中的应用综述

Health data science Pub Date : 2023-02-06 eCollection Date: 2023-01-01 DOI:10.34133/hds.0005
Shuaitong Zhang, Wei Mu, Di Dong, Jingwei Wei, Mengjie Fang, Lizhi Shao, Yu Zhou, Bingxi He, Song Zhang, Zhenyu Liu, Jianhua Liu, Jie Tian
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引用次数: 0

摘要

重要性:消化系统肿瘤(DSN)是导致癌症相关死亡的主要原因,其 5 年生存率不到 20%。内窥镜图像、全切片图像、计算机断层扫描图像和磁共振图像等医学图像的主观评估在消化系统肿瘤的临床实践中发挥着重要作用,但其性能有限,且增加了放射科医生或病理科医生的工作量。人工智能(AI)在医学影像分析中的应用有望增强医学影像的可视化解读,它不仅能将复杂的评估过程自动化,还能将医学影像转化为与肿瘤异质性相关的定量成像特征:我们简要介绍了人工智能医学图像分析的方法,然后回顾了其在食管癌、胃癌、结直肠癌和肝细胞癌等 4 种典型 DSN 上的临床辅助诊断、治疗反应评估和预后预测等临床应用:结论:人工智能技术在支持DSN的临床诊断和治疗决策方面具有巨大潜力。结论:人工智能技术在支持 DSN 临床诊断和治疗决策方面具有巨大潜力,但在将其应用于 DSN 临床实践之前,还需要克服一些技术问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Applications of Artificial Intelligence in Digestive System Neoplasms: A Review.

Importance: Digestive system neoplasms (DSNs) are the leading cause of cancer-related mortality with a 5-year survival rate of less than 20%. Subjective evaluation of medical images including endoscopic images, whole slide images, computed tomography images, and magnetic resonance images plays a vital role in the clinical practice of DSNs, but with limited performance and increased workload of radiologists or pathologists. The application of artificial intelligence (AI) in medical image analysis holds promise to augment the visual interpretation of medical images, which could not only automate the complicated evaluation process but also convert medical images into quantitative imaging features that associated with tumor heterogeneity.

Highlights: We briefly introduce the methodology of AI for medical image analysis and then review its clinical applications including clinical auxiliary diagnosis, assessment of treatment response, and prognosis prediction on 4 typical DSNs including esophageal cancer, gastric cancer, colorectal cancer, and hepatocellular carcinoma.

Conclusion: AI technology has great potential in supporting the clinical diagnosis and treatment decision-making of DSNs. Several technical issues should be overcome before its application into clinical practice of DSNs.

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