Survival Analysis by Penalized Regression and Matrix Factorization
Because every disease has its unique survival pattern, it is necessary to find a suitable model to simulate followups. DNA microarray is a useful technique to detect thousands of gene expressions at one time and is usually employed to classify different types of cancer. We propose combination method...
Saved in:
Main Authors: | Yeuntyng Lai, Morihiro Hayashida, Tatsuya Akutsu |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2013-01-01
|
Series: | The Scientific World Journal |
Online Access: | http://dx.doi.org/10.1155/2013/632030 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Prediction of Protein-Protein Interaction Strength Using Domain Features with Supervised Regression
by: Mayumi Kamada, et al.
Published: (2014-01-01) -
Direct Determination of Smoothing Parameter for Penalized Spline Regression
by: Takuma Yoshida
Published: (2014-01-01) -
Communication-Efficient Modeling with Penalized Quantile Regression for Distributed Data
by: Aijun Hu, et al.
Published: (2021-01-01) -
Firth's penalized logistic regression: A superior approach for analysis of data from India's National Mental Health Survey, 2016
by: Satish Suhas, et al.
Published: (2023-12-01) -
High-Dimensional Cox Regression Analysis in Genetic Studies with Censored Survival Outcomes
by: Jinfeng Xu
Published: (2012-01-01)