| Knowledge-guided multi-task attention network for survival risk prediction using multi-center computed tomography images | |
| Zhang, Liwen1,2; Zhong, Lianzhen1,2; Li, Cong1; Zhang, Wenjuan3; Hu, Chaoen1; Dong, Di1,2; Liu, Zaiyi4; Zhou, Junlin3; Tian, Jie1,5,6,7 | |
| 2022-08-01 | |
| Source Publication | Neural Networks
 |
| ISSN | 0893-6080 |
| Volume | 152Pages:394-406 |
| Abstract | Accurate preoperative prediction of overall survival (OS) risk of human cancers based on CT images is greatly significant for personalized treatment. Deep learning methods have been widely explored to improve automated prediction of OS risk. However, the accuracy of OS risk prediction has been limited by prior existing methods. To facilitate capturing survival-related information, we proposed a novel knowledge-guided multi-task network with tailored attention modules for OS risk prediction and prediction of clinical stages simultaneously. The network exploits useful information contained in multiple learning tasks to improve prediction of OS risk. Three multi-center datasets, including two gastric cancer datasets with 459 patients, and a public American lung cancer dataset with 422 patients, are used to evaluate our proposed network. The results show that our proposed network can boost its performance by capturing and sharing information from other predictions of clinical stages. Our method outperforms the state-of-the-art methods with the highest geometrical metric. Furthermore, our method shows better prognostic value with the highest hazard ratio for stratifying patients into high- and low-risk groups. Therefore, our proposed method may be exploited as a potential tool for the improvement of personalized treatment. © 2022 Elsevier Ltd |
| Keyword | Deep neural networks Diseases Forecasting Computed tomography Computed tomography images Deep learning Human cancer Learning methods Multi tasks Neural-networks Overall survival Risk predictions Task networks |
| Publisher | Elsevier Ltd |
| DOI | 10.1016/j.neunet.2022.04.027 |
| Indexed By | EI |
| Language | 英语 |
| EI Accession Number | 20222212174422 |
| EI Keywords | Computerized tomography |
| EI Classification Number | 461.4 Ergonomics and Human Factors Engineering ; 723.5 Computer Applications |
| Original Document Type | Journal article (JA) |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | https://ir.lzu.edu.cn/handle/262010/481935 |
| Collection | 兰州大学 |
| Corresponding Author | Dong, Di; Liu, Zaiyi |
| Affiliation | 1.CAS Key Laboratory of Molecular Imaging, Beijing Key Laboratory of Molecular Imaging, the State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing; 100190, China; 2.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing; 100049, China; 3.Department of Radiology, Lanzhou University Second Hospital, Lanzhou; 730030, China; 4.Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou; 510080, China; 5.Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine, Beihang University, Beijing; 100191, China; 6.Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Shaanxi, Xi'an; 710126, China; 7.Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology, Beijing; 100191, China |
| Recommended Citation GB/T 7714 | Zhang, Liwen,Zhong, Lianzhen,Li, Cong,et al. Knowledge-guided multi-task attention network for survival risk prediction using multi-center computed tomography images[J]. Neural Networks,2022,152:394-406. |
| APA | Zhang, Liwen.,Zhong, Lianzhen.,Li, Cong.,Zhang, Wenjuan.,Hu, Chaoen.,...&Tian, Jie.(2022).Knowledge-guided multi-task attention network for survival risk prediction using multi-center computed tomography images.Neural Networks,152,394-406. |
| MLA | Zhang, Liwen,et al."Knowledge-guided multi-task attention network for survival risk prediction using multi-center computed tomography images".Neural Networks 152(2022):394-406. |
| Files in This Item: | There are no files associated with this item. | ||||
