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- 2024
-
Mark
Facilitating clinically relevant skin tumor diagnostics with spectroscopy-driven machine learning
(
- Contribution to journal › Article
- 2021
-
Mark
A community effort to identify and correct mislabeled samples in proteogenomic studies
(
- Contribution to journal › Article
- 2019
-
Mark
Establishing strong imputation performance of a denoising autoencoder in a wide range of missing data problems
(
- Contribution to journal › Article
-
Mark
Artificial neural network models to predict nodal status in clinically node-negative breast cancer
(
- Contribution to journal › Article
- 2018
-
Mark
A multicenter study investigating the molecular fingerprint of psychological resilience in breast cancer patients : Study protocol of the SCAN-B resilience study
(
- Contribution to journal › Article
-
Mark
Identification and validation of single-sample breast cancer radiosensitivity gene expression predictors
(
- Contribution to journal › Article
- 2015
-
Mark
Finding Risk Groups by Optimizing Artificial Neural Networks on the Area under the Survival Curve Using Genetic Algorithms
(
- Contribution to journal › Article
-
Mark
Single-Cell Network Analysis Identifies DDIT3 as a Nodal Lineage Regulator in Hematopoiesis.
(
- Contribution to journal › Article
- 2014
-
Mark
SOX11 and TP53 add prognostic information to MIPI in a homogenously treated cohort of mantle cell lymphoma - a Nordic Lymphoma Group study.
(
- Contribution to journal › Article
- 2013
-
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