Radiomics in glioblastoma: current status and challenges facing clinical implementation A Chaddad, MJ Kucharczyk, P Daniel, S Sabri, BJ Jean-Claude, T Niazi, ... Frontiers in oncology 9, 374, 2019 | 160 | 2019 |
Survey of explainable AI techniques in healthcare A Chaddad, J Peng, J Xu, A Bouridane Sensors 23 (2), 634, 2023 | 157 | 2023 |
Temozolomide induced hypermutation in glioma: evolutionary mechanisms and therapeutic opportunities P Daniel, S Sabri, A Chaddad, B Meehan, B Jean-Claude, J Rak, ... Frontiers in Oncology 9, 41, 2019 | 145 | 2019 |
Automated Feature Extraction in brain Tumor by Magnetic Resonance Imaging Using Gaussian Mixture Models A Chaddad International Journal of Biomedical Imaging, 11, 2015 | 123 | 2015 |
Hippocampus and amygdala radiomic biomarkers for the study of autism spectrum disorder A Chaddad, C Desrosiers, L Hassan, C Tanougast BMC neuroscience 18, 1-12, 2017 | 107 | 2017 |
Multimodal radiomic features for the predicting gleason score of prostate cancer A Chaddad, MJ Kucharczyk, T Niazi Cancers 10 (8), 249, 2018 | 101 | 2018 |
Prediction of survival with multi-scale radiomic analysis in glioblastoma patients A Chaddad, S Sabri, T Niazi, B Abdulkarim Medical & biological engineering & computing 56, 2287-2300, 2018 | 83 | 2018 |
Deep radiomic analysis of MRI related to Alzheimer’s disease A Chaddad, C Desrosiers, T Niazi IEEE access 6 (1), 58213-58221, 2018 | 78 | 2018 |
Quantitative evaluation of robust skull stripping and tumor detection applied to axial MR images A Chaddad, C Tanougast Brain Informatics 3, 53–61, 2016 | 78 | 2016 |
Predicting Gleason score of prostate cancer patients using radiomic analysis A Chaddad, T Niazi, S Probst, F Bladou, M Anidjar, B Bahoric Frontiers in oncology 8, 630, 2018 | 74 | 2018 |
Novel radiomic features based on joint intensity matrices for predicting glioblastoma patient survival time A Chaddad, P Daniel, C Desrosiers, M Toews, B Abdulkarim IEEE journal of biomedical and health informatics 23 (2), 795-804, 2018 | 74 | 2018 |
Predicting survival time of lung cancer patients using radiomic analysis A Chaddad, C Desrosiers, M Toews, B Abdulkarim Oncotarget 8 (61), 104393, 2017 | 72 | 2017 |
Classifications of multispectral colorectal cancer tissues using convolution neural network H Haj-Hassan, A Chaddad, Y Harkouss, C Desrosiers, M Toews, ... Journal of pathology informatics 8 (1), 1, 2017 | 63 | 2017 |
Extracted magnetic resonance texture features discriminate between phenotypes and are associated with overall survival in glioblastoma multiforme patients A Chaddad, C Tanougast Medical & biological engineering & computing 54, 1707-1718, 2016 | 62 | 2016 |
Glioma grading via analysis of digital pathology images using machine learning S Rathore, T Niazi, MA Iftikhar, A Chaddad Cancers 12 (3), 578, 2020 | 58 | 2020 |
Multi-scale radiomic analysis of sub-cortical regions in MRI related to autism, gender and age A Chaddad, C Desrosiers, M Toews Scientific reports 7 (1), 45639, 2017 | 57 | 2017 |
Deep CNN models for predicting COVID-19 in CT and x-ray images A Chaddad, L Hassan, C Desrosiers Journal of medical imaging 8 (S1), 014502-014502, 2021 | 51 | 2021 |
Radiomics evaluation of histological heterogeneity using multiscale textures derived from 3D wavelet transformation of multispectral images A Chaddad, P Daniel, T Niazi Frontiers in oncology 8, 96, 2018 | 51 | 2018 |
Integration of radiomic and multi-omic analyses predicts survival of newly diagnosed IDH1 wild-type glioblastoma A Chaddad, P Daniel, S Sabri, C Desrosiers, B Abdulkarim Cancers 11 (8), 1148, 2019 | 49 | 2019 |
Multi texture analysis of colorectal cancer continuum using multispectral imagery A Chaddad, C Desrosiers, A Bouridane, M Toews, L Hassan, ... PloS one 11 (2), e0149893, 2016 | 49 | 2016 |