人工智能在肺腺癌病理学亚型分型及基因表达分析中应用的研究进展  

Research progress of artificial intelligence in pathological subtypes classification and gene expression analysis of lung adenocarcinoma

作　　者：周连田 赵可辉[1] 张志强[1] ZHOU Liantian;ZHAO Kehui;ZHANG Zhiqiang(College of Intelligence and Information Engineering,Shandong University of Traditional Chinese Medicine,Jinan,250300,P.R.China;Heze Traditional Chinese Medicine Hospital,Heze,274000,Shandong,P.R.China)

机构地区：[1]山东中医药大学智能与信息工程学院,济南250300 [2]菏泽市中医医院,山东菏泽274000

出　　处：《中国胸心血管外科临床杂志》2024年第1期145-152,共8页Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

基　　金：山东省中医药科技项目(M-2022139)。

摘　　要：肺腺癌是非小细胞肺癌的一种普遍组织学亚型,具有不同的形态学和分子特征,这对预后和治疗计划至关重要。近年来,随着人工智能技术的发展,其在肺腺癌病理学亚型及基因表达研究中的应用得到了广泛关注。本文综述了机器学习和深度学习在肺腺癌病理学亚型分型及基因表达分析中应用的研究进展,总结现阶段存在的一些问题和挑战,并展望了人工智能在肺腺癌研究中的未来发展方向。Lung adenocarcinoma is a prevalent histological subtype of non-small cell lung cancer with different morphologic and molecular features that are critical for prognosis and treatment planning.In recent years,with the development of artificial intelligence technology,its application in the study of pathological subtypes and gene expression of lung adenocarcinoma has gained widespread attention.This paper reviews the research progress of machine learning and deep learning in pathological subtypes classification and gene expression analysis of lung adenocarcinoma,and some problems and challenges at the present stage are summarized and the future directions of artificial intelligence in lung adenocarcinoma research are foreseen.

关 键 词：肺腺癌 病理学亚型 基因表达 人工智能 机器学习 深度学习 综述 

分 类 号：R734.2[医药卫生—肿瘤]