| Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach HJWL Aerts, ER Velazquez, RTH Leijenaar, C Parmar, P Grossmann, ... Nature communications 5 (1), 4006, 2014 | 5788 | 2014 |
| Machine learning methods for quantitative radiomic biomarkers C Parmar, P Grossmann, J Bussink, P Lambin, HJWL Aerts Scientific reports 5 (1), 13087, 2015 | 1200 | 2015 |
| CT-based radiomic signature predicts distant metastasis in lung adenocarcinoma TP Coroller, P Grossmann, Y Hou, ER Velazquez, RTH Leijenaar, ... Radiotherapy and Oncology 114 (3), 345-350, 2015 | 852 | 2015 |
| Deep learning for lung cancer prognostication: a retrospective multi-cohort radiomics study A Hosny, C Parmar, TP Coroller, P Grossmann, R Zeleznik, A Kumar, ... PLoS medicine 15 (11), e1002711, 2018 | 623 | 2018 |
| Radiomic feature clusters and prognostic signatures specific for lung and head & neck cancer C Parmar, RTH Leijenaar, P Grossmann, E Rios Velazquez, J Bussink, ... Scientific reports 5 (1), 11044, 2015 | 532 | 2015 |
| Radiomic machine-learning classifiers for prognostic biomarkers of head and neck cancer C Parmar, P Grossmann, D Rietveld, MM Rietbergen, P Lambin, ... Frontiers in oncology 5, 272, 2015 | 453 | 2015 |
| Exploratory study to identify radiomics classifiers for lung cancer histology W Wu, C Parmar, P Grossmann, J Quackenbush, P Lambin, J Bussink, ... Frontiers in oncology 6, 71, 2016 | 446 | 2016 |
| Defining the biological basis of radiomic phenotypes in lung cancer P Grossmann, O Stringfield, N El-Hachem, MM Bui, E Rios Velazquez, ... elife 6, e23421, 2017 | 399 | 2017 |
| Radiomic phenotype features predict pathological response in non-small cell lung cancer TP Coroller, V Agrawal, V Narayan, Y Hou, P Grossmann, SW Lee, ... Radiotherapy and oncology 119 (3), 480-486, 2016 | 382 | 2016 |
| Integration of TP53, DREAM, MMB-FOXM1 and RB-E2F target gene analyses identifies cell cycle gene regulatory networks M Fischer, P Grossmann, M Padi, JA DeCaprio Nucleic Acids Research, gkw523, 2016 | 379 | 2016 |
| PharmacoGx: an R package for analysis of large pharmacogenomic datasets BHK Petr Smirnov, Zhaleh Safikhani, Nehme El-Hachem, Dong Wang, Adrian She ... Bioinformatics 32 (8), 1244-1246, 2015 | 321* | 2015 |
| Data from NSCLC-radiomics-genomics HJWL Aerts, E Rios Velazquez, RTH Leijenaar, C Parmar, P Grossmann, ... (No Title), 2015 | 245 | 2015 |
| Defining a radiomic response phenotype: a pilot study using targeted therapy in NSCLC HJWL Aerts, P Grossmann, Y Tan, GR Oxnard, N Rizvi, LH Schwartz, ... Scientific reports 6 (1), 33860, 2016 | 244 | 2016 |
| Corrigendum: Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach HJWL Aerts, ER Velazquez, RTH Leijenaar, C Parmar, P Grossmann, ... Nature communications 5, 4644, 2014 | 170 | 2014 |
| Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nat Commun. 2014; 5: 4006 HJ Aerts, ER Velazquez, RT Leijenaar, C Parmar, P Grossmann, ... | 156 | 2014 |
| Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nat Commun 5: 4006 HJ Aerts, ER Velazquez, RT Leijenaar, C Parmar, P Grossmann, ... | 144 | 2014 |
| Somatic mutations associated with MRI-derived volumetric features in glioblastoma DA Gutman, WD Dunn Jr, P Grossmann, LAD Cooper, CA Holder, ... Neuroradiology 57 (12), 1227-1237, 2015 | 124 | 2015 |
| Quantitative imaging biomarkers for risk stratification of patients with recurrent glioblastoma treated with bevacizumab P Grossmann, V Narayan, K Chang, R Rahman, L Abrey, DA Reardon, ... Neuro-oncology 19 (12), 1688-1697, 2017 | 117 | 2017 |
| Imaging-genomics reveals driving pathways of MRI derived volumetric tumor phenotype features in Glioblastoma P Grossmann, DA Gutman, WD Dunn Jr, CA Holder, HJWL Aerts BMC cancer 16 (1), 611, 2016 | 94 | 2016 |
| Machine learning methods for quantitative radiomic biomarkers. Sci Rep 5: 13087 C Parmar, P Grossmann, J Bussink, P Lambin, H Aerts | 54 | 2015 |
Hugo AertsProfessor, Harvard | Director, AI in Medicine Program, Mass General Brigham | Professor, MaastrichtUVerified email at dfci.harvard.edu
