Prognostic prediction of lung adenocarcinoma based on transcriptomic data and stacked supervised autoencoder

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...

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Bibliographic Details
Main Authors: LI Pengpeng, CHEN Xicheng, HUANG Jinyu, WU Yazhou
Format: Article
Language:zho
Published: Editorial Office of Journal of Army Medical University 2023-03-01
Series:陆军军医大学学报
Subjects:
lung adenocarcinoma
transcriptomics
prognostic prediction
cox regression
autoencoder
Online Access:http://aammt.tmmu.edu.cn/html/202212025.htm

Internet

http://aammt.tmmu.edu.cn/html/202212025.htm

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