Prognostic prediction of lung adenocarcinoma based on transcriptomic data and stacked supervised autoencoder
Objective To build a stacked supervised autoencoder (SSAE) model based on transcriptomic data, so as to improve the prognostic prediction of lung adenocarcinoma (LUAD). Methods Transcriptomic data (475 samples and 25 481 genes) from the Cancer Genome Atlas (TCGA) database were collected, and the sur...
Main Authors: | LI Pengpeng, CHEN Xicheng, HUANG Jinyu, WU Yazhou |
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Format: | Article |
Language: | zho |
Published: |
Editorial Office of Journal of Army Medical University
2023-03-01
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Series: | 陆军军医大学学报 |
Subjects: | |
Online Access: | http://aammt.tmmu.edu.cn/html/202212025.htm |
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