Regularized Survival Models
Regularized Survival Models is a class of statistical models in survival analysis that incorporates penalty terms to constrain model complexity, thereby improving generalization by reducing overfitting in the estimation of time-to-event outcomes.
41
Publications
3K
Citations
142
Authors
88
Institutions
Publications per year
2017–2026
16
Variants
Penalized Survival Models
Parents
41
Boosting Algorithms: Regularization, Prediction and Model Fitting
Statistical Science · 2007 · 738 citations · Full text
BOOSTING ALGORITHMS: REGULARIZATION, PREDICTION AND MODEL FITTING
2007 · 706 citations
Group Lasso Regularized Deep Learning for Cancer Prognosis from Multi-Omics and Clinical Features
Gangcai Xie, Chengliang Dong, Yinfei Kong et al. · Genes · 2019 · 109 citations · Full text
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Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento, Portugal
2 publications · 44 citations
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1–5 of 142
88
Wayne State University
Detroit, United States
3 h-index
5 publications
194 citations
Stanford University
Stanford, United States
3 h-index
14 publications
363 citations
University of Michigan
Ann Arbor, United States
3 h-index
5 publications
222 citations
Universitätsmedizin Göttingen
Göttingen, Germany
2 h-index
4 publications
113 citations

Children's National
Washington, United States
2 h-index
3 publications
104 citations
Macau University of Science and Technology
Macao, Macao
2 h-index
6 publications
126 citations
Rutgers, The State University of New Jersey
New Brunswick, United States
2 h-index
5 publications
82 citations

University of York
York, United Kingdom
2 h-index
2 publications
59 citations
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4 publications · 153 citations
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3 publications · 106 citations
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2 publications · 49 citations
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2 publications · 64 citations
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2 publications · 35 citations
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