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Technol Health Care. 2019 Apr 26. doi: 10.3233/THC-199009. [Epub ahead of print]

A novel log penalty in a path seeking scheme for biomarker selection.

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Faculty of Information Technology, Macau University of Science and Technology, Macau, China.
State Key Laboratory of Quality Research in Chinese Medicines, Macau University of Science and Technology, Macau, China.


Biomarker selection or feature selection from survival data is a topic of considerable interest. Recently various survival analysis approaches for biomarker selection have been developed; however, there are growing challenges to currently methods for handling high-dimensional and low-sample problem. We propose a novel Log-sum regularization estimator within accelerated failure time (AFT) for predicting cancer patient survival time with a few biomarkers. This approach is implemented in path seeking algorithm to speed up solving the Log-sum penalty. Additionally, the control parameter of Log-sum penalty is modified by bayesian information criterion (BIC). The results indicate that our proposed approach is able to achieve good performance in both simulated and real datasets with other ℓ1 type regularization methods for biomarker selection.


Biomarker selection; Log-sum regularization; bayesian information criterion; path seeking scheme


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