The value of AI in the Diagnosis, Treatment, and Prognosis of Malignant Lung Cancer

被引：4

作者：

Wang, Yue ^{[1
]}

Cai, Haihua ^{[2
]}

Pu, Yongzhu ^{[1
]}

Li, Jindan ^{[1
]}

Yang, Fake ^{[1
]}

Yang, Conghui ^{[1
]}

Chen, Long ^{[1
]}

Hu, Zhanli ^{[2
]}

机构：

[1] Kunming Med Univ, Affiliated Hosp 3, Yunnan Canc Hosp, Dept PET,CT Ctr,Canc Ctr Yunnan Prov, Kunming, Peoples R China

[2] Chinese Acad Sci, Lauterbur Res Ctr Biomed Imaging, Shenzhen Inst Adv Technol, Shenzhen, Peoples R China

来源：

FRONTIERS IN RADIOLOGY | 2022年 / 2卷

基金：

中国博士后科学基金; 中国国家自然科学基金;

关键词：

lung cancer; AI; CAD; deep learning; radiomics; COMPUTER-AIDED DIAGNOSIS; RISK-FACTORS; CLASSIFICATION; NODULES; IMAGES; TEXTURE; RADIOTHERAPY; EXPRESSION; FEATURES; THERAPY;

D O I：

10.3389/fradi.2022.810731

中图分类号：

R8 [特种医学]; R445 [影像诊断学];

学科分类号：

1002 ; 100207 ; 1009 ;

摘要：

Malignant tumors is a serious public health threat. Among them, lung cancer, which has the highest fatality rate globally, has significantly endangered human health. With the development of artificial intelligence (AI) and its integration with medicine, AI research in malignant lung tumors has become critical. This article reviews the value of CAD, computer neural network deep learning, radiomics, molecular biomarkers, and digital pathology for the diagnosis, treatment, and prognosis of malignant lung tumors.

引用

页数：12

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