- •MC study showed limitation of correlation coefficients in multi-class classification.
- •Explanation of why categorical outcome prediction requires special consideration.
- •MC simulation designed to show shortcoming of surrogate biomarkers in clinical trails.
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- Radiomics: images are more than pictures, they are data.Radiology. 2016; 278: 563-577
- Quantitative radiomics studies for tissue characterization: a review of technology and methodological procedures.Br J Radiol. 2017; 90: 20160665
- Beyond imaging: the promise of radiomics.Phys Med. 2017; 38: 122-139
- Radiomics in radiooncology–challenging the medical physicist.Phys Med. 2018; 48: 27-36
- A radiomics model from joint FDG-PET and MRI texture features for the prediction of lung metastases in soft-tissue sarcomas of the extremities.Phys Med Biol. 2015; 60: 5471
- Machine learning methods for quantitative radiomic biomarkers.Sci Rep. 2015; 5: 13087
- Relaxing the rule of ten events per variable in logistic and Cox regression.Am J Epidemiol. 2007; 165: 710-718
- An empirical approach for avoiding false discoveries when applying high-dimensional radiomics to small datasets.IEEE TRPMS. 2018; 3: 201-209
- A simple generalisation of the area under the ROC curve for multiple class classification problems.Mach Learn. 2001; 45: 171-186
- Radiomics of brain MRI: utility in prediction of metastatic tumor type.Radiology. 2018; 290: 479-487
- Classifying brain metastases by their primary site of origin using a radiomics approach based on texture analysis: a feasibility study.Eur Radiol. 2018; 28: 4514-4523
- Deciphering unclassified tumors of non-small-cell lung cancer through radiomics.Comput Biol Med. 2017; 91: 222-230
- Machine-learning based radiogenomics analysis of MRI features and metagenes in glioblastoma multiforme patients with different survival time.J Cell Mol Med. 2019; 23: 4375-4385
- The diagnostic value of radiomics-based machine learning in predicting the grade of meningiomas using conventional magnetic resonance imaging: a preliminary study.Front Oncol. 2019; 9: 1338
- Volume under the ROC surface for multi-class problems.in: ECML. Springer, Berlin, Heidelberg2003: 108-120
Glass GV, Hopkins KD. Statistical methods in education and psychology (3rd ed.). Allyn & Bacon; 1995. ISBN 0-205-14212-5.
- Measures of association: how to choose?.J Diagn Med Sonogr. 2008; 24: 155-162
- Filter methods for feature selection–a comparative study.in: IDEAL. Springer, Berlin, Heidelberg2007: 178-187
- Ct radiomic features of pancreatic neuroendocrine neoplasms (panNEN) are robust against delineation uncertainty.Phys Med. 2019; 57: 41-46