D. de Ruysscher

Radiology, Nuclear Medicine and Imaging · 2017–2019

A researcher in the Science corpus: 3 papers; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom D. de Ruysscher trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Robert Tibshirani
  2. El Naqa
  3. Chintan Parmar

Papers from D. de Ruysscher's perspective

Ordered by how strongly the researchers D. de Ruysscher trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Radiomics: Extracting more information from medical images using advanced feature analysis (European Journal of Cancer)
  2. QIN “Radiomics: The Process and the Challenges” (Magnetic Resonance Imaging)
  3. Machine Learning methods for Quantitative Radiomic Biomarkers (Scientific Reports)
  4. Decoding global gene expression programs in liver cancer by noninvasive imaging (Nature Biotechnology)
  5. The effect of SUV discretization in quantitative FDG-PET Radiomics: the need for standardized methodology in tumor texture analysis (Scientific Reports)
  6. CT-based radiomic signature predicts distant metastasis in lung adenocarcinoma. (Radiotherapy and Oncology)
  7. Radiomics: Images Are More than Pictures, They Are Data (Radiology)
  8. Regression Shrinkage and Selection via the Lasso
  9. Radiomic Machine-Learning Classifiers for Prognostic Biomarkers of Head and Neck Cancer (Frontiers in Oncology)
  10. Modeling Survival Data: Extending the Cox Model

Their papers