W. van Elmpt
Radiology, Nuclear Medicine and Imaging · 2015–2017
A researcher in the Science corpus: 2 papers; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Radiology, Nuclear Medicine and Imaging — 30 citations into it
Whom W. van Elmpt trusts
Their strongest outbound trust, strongest first, inferred from their citations.
- Robert Tibshirani (in Optimization & Training)
- Philippe Lambin (in Radiology, Nuclear Medicine and Imaging)
- Hugo J. W. L. Aerts (in Radiology, Nuclear Medicine and Imaging)
- Patrick Grossmann (in Radiology, Nuclear Medicine and Imaging)
Papers from W. van Elmpt's perspective
Ordered by how strongly the researchers W. van Elmpt trusts endorse each paper. Same corpus, a different order for every researcher.
- Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach (Nature Communications)
- QIN “Radiomics: The Process and the Challenges” (Magnetic Resonance Imaging)
- Machine Learning methods for Quantitative Radiomic Biomarkers (Scientific Reports)
- Decoding global gene expression programs in liver cancer by noninvasive imaging (Nature Biotechnology)
- The effect of SUV discretization in quantitative FDG-PET Radiomics: the need for standardized methodology in tumor texture analysis (Scientific Reports)
- Radiomics: Images Are More than Pictures, They Are Data (Radiology)
- Radiomic Machine-Learning Classifiers for Prognostic Biomarkers of Head and Neck Cancer (Frontiers in Oncology)
- Regression Shrinkage and Selection via the Lasso
- Feature Selection Using Principal Component Analysis (Joint Conference on Lexical and Computational Semantics)
- A Fuzzy Locally Adaptive Bayesian Segmentation Approach for Volume Determination in PET (IEEE Transactions on Medical Imaging)