Progress in the application of deep learning in prognostic models for non-small cell lung cancer
- VernacularTitle:深度学习在非小细胞肺癌预后模型中的应用进展
- Author:
Ruikang ZHONG
1
;
Jinghua LI
1
;
Ximing LIN
1
;
Xueni FANG
1
;
Kaiwen HU
2
;
Tian ZHOU
2
Author Information
1. 1. Beijing University of Chinese Medicine, Beijing, 100105, P. R. China 2. Dongfang Hospital, Beijing University of Chinese Medicine, Beijing, 100078, P. R. China
2. Dongfang Hospital, Beijing University of Chinese Medicine, Beijing, 100078, P. R. China
- Publication Type:Journal Article
- Keywords:
Deep learning;
non-small cell lung cancer;
prognostic model;
precision medicine;
review
- From:
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery
2024;31(09):1345-1350
- CountryChina
- Language:Chinese
-
Abstract:
Non-small cell lung cancer is one of the cancers with the highest incidence and mortality rate in the world, and precise prognostic models can guide clinical treatment plans. With the continuous upgrading of computer technology, deep learning as a breakthrough technology of artificial intelligence has shown good performance and great potential in the application of non-small cell lung cancer prognosis model. The research on the application of deep learning in survival and recurrence prediction, efficacy prediction, distant metastasis prediction, and complication prediction of non-small cell lung cancer has made some progress, and it shows a trend of multi-omics and multi-modal joint, but there are still shortcomings, which should be further explored in the future to strengthen model verification and solve practical problems in clinical practice.
