A Novel Attention-Mechanism Based Cox Survival Model by Exploiting Pan-Cancer Empirical Genomic Information
文献类型：期刊论文
| 作者 | Meng, Xiangyu1; Wang, Xun1,2; Zhang, Xudong1; Zhang, Chaogang1; Zhang, Zhiyuan1; Zhang, Kuijie1; Wang, Shudong1 |
| 刊名 | CELLS
 |
| 出版日期 | 2022-05-01 |
| 卷号 | 11期号:9页码:18 |
| 关键词 | deep learning survival analysis neural networks Cox regression cancer prognosis |
| DOI | 10.3390/cells11091421 |
| 英文摘要 | Cancer prognosis is an essential goal for early diagnosis, biomarker selection, and medical therapy. In the past decade, deep learning has successfully solved a variety of biomedical problems. However, due to the high dimensional limitation of human cancer transcriptome data and the small number of training samples, there is still no mature deep learning-based survival analysis model that can completely solve problems in the training process like overfitting and accurate prognosis. Given these problems, we introduced a novel framework called SAVAE-Cox for survival analysis of high-dimensional transcriptome data. This model adopts a novel attention mechanism and takes full advantage of the adversarial transfer learning strategy. We trained the model on 16 types of TCGA cancer RNA-seq data sets. Experiments show that our module outperformed state-of-the-art survival analysis models such as the Cox proportional hazard model (Cox-ph), Cox-lasso, Cox-ridge, Cox-nnet, and VAECox on the concordance index. In addition, we carry out some feature analysis experiments. Based on the experimental results, we concluded that our model is helpful for revealing cancer-related genes and biological functions. |
| 资助项目 | National Natural Science Foundation of China[61873280] ; National Natural Science Foundation of China[61873281] ; National Natural Science Foundation of China[61972416] ; Natural Science Foundation of Shandong Province[ZR2019MF012] |
| WOS研究方向 | Cell Biology |
| 语种 | 英语 |
| WOS记录号 | WOS:000794779100001 |
| 出版者 | MDPI |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/19542]  |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Wang, Shudong |
| 作者单位 | 1.China Univ Petr, Coll Comp Sci & Technol, Qingdao Inst Software, Qingdao 266580, Peoples R China 2.Chinese Acad Sci, China High Performance Comp Res Ctr, Inst Comp Technol, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Meng, Xiangyu,Wang, Xun,Zhang, Xudong,et al. A Novel Attention-Mechanism Based Cox Survival Model by Exploiting Pan-Cancer Empirical Genomic Information[J]. CELLS,2022,11(9):18. |
| APA | Meng, Xiangyu.,Wang, Xun.,Zhang, Xudong.,Zhang, Chaogang.,Zhang, Zhiyuan.,...&Wang, Shudong.(2022).A Novel Attention-Mechanism Based Cox Survival Model by Exploiting Pan-Cancer Empirical Genomic Information.CELLS,11(9),18. |
| MLA | Meng, Xiangyu,et al."A Novel Attention-Mechanism Based Cox Survival Model by Exploiting Pan-Cancer Empirical Genomic Information".CELLS 11.9(2022):18. |
入库方式： OAI收割
来源：计算技术研究所
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