Prediction of Second Primary Lung Cancer Patient’s Survivability Based on Improved Eigenvector Centrality-Based Feature Selection

Prediction of Second Primary Lung Cancer Patient’s Survivability Based on Improved Eigenvector Centrality-Based Feature Selection

Modeling of second primary lung cancer (SPLC) patients’ survival prediction has important theoretical significance and practical needs. Cancer survivability prediction may provide advice for better clinical decisions and personalized medicine. The Surveillance, Epidemiology, and End Resul...

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Bibliographic Details
Main Authors: Peng Liu, Kexin Jin, Yiping Jiao, Mutian He, Shumin Fei
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Second primary lung cancer
cancer survival prediction
improved eigenvector centrality-based feature selection
Online Access:https://ieeexplore.ieee.org/document/9370095/

Internet

https://ieeexplore.ieee.org/document/9370095/

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