Advances in artificial intelligence applications in the field of lung cancer

被引:0
|
作者
Yang, Di [1 ,2 ]
Miao, Yafei [1 ,2 ]
Liu, Changjiang [3 ]
Zhang, Nan [3 ]
Zhang, Duo [2 ]
Guo, Qiang [2 ]
Gao, Shuo [4 ,5 ]
Li, Linqian [4 ,6 ,7 ]
Wang, Jianing [8 ]
Liang, Si [4 ,6 ]
Li, Peng [4 ,6 ]
Bai, Xuan [4 ,6 ]
Zhang, Ke [2 ,4 ,6 ,7 ]
机构
[1] Hebei Univ, Affiliated Hosp, Clin Med Coll, Baoding, Peoples R China
[2] Hebei Univ, Affiliated Hosp, Thorac Surg Dept, Baoding, Peoples R China
[3] Hebei Med Univ, Hosp 4, Thorac Surg Dept, Shijiazhuang, Peoples R China
[4] Hebei Univ, Affiliated Hosp, Basic Res Key Lab Gen Surg Digital Med, Baoding, Peoples R China
[5] Hebei Univ, Affiliated Hosp, Informat Ctr, Baoding, Peoples R China
[6] Hebei Univ, Inst Life Sci & Green Dev, Baoding, Peoples R China
[7] Hebei Univ, Affiliated Hosp, 3D Image & 3D Printing Ctr, Baoding, Peoples R China
[8] Hebei Univ, Affiliated Hosp, Dept Radiol, Baoding, Peoples R China
来源
FRONTIERS IN ONCOLOGY | 2024年 / 14卷
关键词
artificial intelligence; lung cancer; machine learning; deep learning; convolutional neural network; EPIDEMIOLOGY; MUTATIONS;
D O I
10.3389/fonc.2024.1449068
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Lung cancer remains a leading cause of cancer-related deaths globally, with its incidence steadily rising each year, representing a significant threat to human health. Early detection, diagnosis, and timely treatment play a crucial role in improving survival rates and reducing mortality. In recent years, significant and rapid advancements in artificial intelligence (AI) technology have found successful applications in various clinical areas, especially in the diagnosis and treatment of lung cancer. AI not only improves the efficiency and accuracy of physician diagnosis but also aids in patient treatment and management. This comprehensive review presents an overview of fundamental AI-related algorithms and highlights their clinical applications in lung nodule detection, lung cancer pathology classification, gene mutation prediction, treatment strategies, and prognosis. Additionally, the rapidly advancing field of AI-based three-dimensional (3D) reconstruction in lung cancer surgical resection is discussed. Lastly, the limitations of AI and future prospects are addressed.
引用
收藏
页数:10
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