Gene selection in Cox regression model based on a new adaptive penalized method

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Summary

An adaptive penalized Cox proportional hazards regression model is proposed, with the aim of identification relevant genes and provides high classification accuracy, by combining the Cox proportional hazard regression model with the weighted least absolute shrinkage and selection operator (LASSO) method.

Type
article
Published
2020-05-15
Cited by
0
References
37
Access
Open access

Keywords

Proportional hazards model, Lasso (programming language), Regression, Regression analysis, Selection (genetic algorithm)

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