R. Larue

Radiology, Nuclear Medicine and Imaging · 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

Whom R. Larue trusts overall

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

  1. Robert Tibshirani
  2. El Naqa
  3. Chintan Parmar
  4. Patrick Grossmann
  5. Ron Kohavi
  6. Hugo J. W. L. Aerts
  7. Piotr M. Szczypiński
  8. Mathieu Hatt
  9. Philippe Lambin
  10. George H. John

Papers from R. Larue's perspective

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

  1. Machine Learning methods for Quantitative Radiomic Biomarkers (Scientific Reports)
  2. Regression Shrinkage and Selection via the Lasso
  3. Radiomic Machine-Learning Classifiers for Prognostic Biomarkers of Head and Neck Cancer (Frontiers in Oncology)
  4. Feature Selection Using Principal Component Analysis (Joint Conference on Lexical and Computational Semantics)
  5. A radiomics model from joint FDG-PET and MRI texture features for the prediction of lung metastases in soft-tissue sarcomas of the extremities
  6. A Fuzzy Locally Adaptive Bayesian Segmentation Approach for Volume Determination in PET (IEEE Transactions on Medical Imaging)
  7. From signatures to models: understanding cancer using microarrays (Nature Genetics)
  8. Controlling the false discovery rate: a practical and powerful approach to multiple testing
  9. Combining radiotherapy and cancer immunotherapy: a paradigm shift. (Journal of the National Cancer Institute)
  10. Molecular and genetic properties of tumors associated with local immune cytolytic activity (Cell)

Their papers