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- 2019
-
Mark
Artificial neural network models to predict nodal status in clinically node-negative breast cancer
(
- Contribution to journal › Article
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Mark
Establishing strong imputation performance of a denoising autoencoder in a wide range of missing data problems
(
- Contribution to journal › Article
- 2015
-
Mark
Single-Cell Network Analysis Identifies DDIT3 as a Nodal Lineage Regulator in Hematopoiesis.
(
- Contribution to journal › Article
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Mark
Finding Risk Groups by Optimizing Artificial Neural Networks on the Area under the Survival Curve Using Genetic Algorithms
(
- Contribution to journal › Article
- 2013
-
Mark
Transcriptional regulation of lineage commitment - a stochastic model of cell fate decisions.
(
- Contribution to journal › Article
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Mark
Training artificial neural networks directly on the concordance index for censored data using genetic algorithms.
(
- Contribution to journal › Article
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Mark
Ensembles of genetically trained artificial neural networks for survival analysis
2013) 21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2013 p.333-338(
- Chapter in Book/Report/Conference proceeding › Paper in conference proceeding
- 2006
-
Mark
Gene expression profilers and conventional clinical markers to predict distant recurrences for premenopausal breast cancer patients after adjuvant chemotherapy.
(
- Contribution to journal › Article