| A machine learning approach to radiogenomics of breast cancer: a study of 922 subjects and 529 DCE-MRI features A Saha, MR Harowicz, LJ Grimm, CE Kim, SV Ghate, R Walsh, ... British journal of cancer 119 (4), 508-516, 2018 | 341 | 2018 |
| Multivariate machine learning models for prediction of pathologic response to neoadjuvant therapy in breast cancer using MRI features: a study using an independent validation set EH Cain, A Saha, MR Harowicz, JR Marks, PK Marcom, MA Mazurowski Breast cancer research and treatment 173 (2), 455-463, 2019 | 228 | 2019 |
| Deep learning for identifying radiogenomic associations in breast cancer Z Zhu, E Albadawy, A Saha, J Zhang, MR Harowicz, MA Mazurowski Computers in biology and medicine 109, 85-90, 2019 | 188 | 2019 |
| Dynamic contrast-enhanced magnetic resonance images of breast cancer patients with tumor locations [Data set] A Saha, MR Harowicz, LJ Grimm, J Weng, EH Cain, CE Kim, SV Ghate, ... The Cancer Imaging Archive 10, 2021 | 77 | 2021 |
| Breast cancer MRI radiomics: An overview of algorithmic features and impact of inter‐reader variability in annotating tumors A Saha, MR Harowicz, MA Mazurowski Medical physics 45 (7), 3076-3085, 2018 | 71 | 2018 |
| Deep learning analysis of breast MRIs for prediction of occult invasive disease in ductal carcinoma in situ Z Zhu, M Harowicz, J Zhang, A Saha, LJ Grimm, ES Hwang, ... Computers in biology and medicine 115, 103498, 2019 | 63 | 2019 |
| A study of association of Oncotype DX recurrence score with DCE-MRI characteristics using multivariate machine learning models A Saha, MR Harowicz, W Wang, MA Mazurowski Journal of cancer research and clinical oncology 144 (5), 799-807, 2018 | 53 | 2018 |
| Algorithms for prediction of the Oncotype DX recurrence score using clinicopathologic data: a review and comparison using an independent dataset MR Harowicz, TJ Robinson, MA Dinan, A Saha, JR Marks, PK Marcom, ... Breast cancer research and treatment 162 (1), 1-10, 2017 | 48 | 2017 |
| Can algorithmically assessed MRI features predict which patients with a preoperative diagnosis of ductal carcinoma in situ are upstaged to invasive breast cancer? MR Harowicz, A Saha, LJ Grimm, PK Marcom, JR Marks, ES Hwang, ... Journal of magnetic resonance imaging 46 (5), 1332-1340, 2017 | 32 | 2017 |
| Interobserver variability in identification of breast tumors in MRI and its implications for prognostic biomarkers and radiogenomics A Saha, LJ Grimm, M Harowicz, SV Ghate, C Kim, R Walsh, ... Medical physics 43 (8Part1), 4558-4564, 2016 | 29 | 2016 |
| Association of distant recurrence‐free survival with algorithmically extracted MRI characteristics in breast cancer MA Mazurowski, A Saha, MR Harowicz, EH Cain, JR Marks, PK Marcom Journal of Magnetic Resonance Imaging 49 (7), e231-e240, 2019 | 26 | 2019 |
| Intra-tumor molecular heterogeneity in breast cancer: definitions of measures and association with distant recurrence-free survival A Saha, MR Harowicz, EH Cain, AH Hall, ESS Hwang, JR Marks, ... Breast cancer research and treatment 172 (1), 123-132, 2018 | 14 | 2018 |
| Dynamic contrast-enhanced magnetic resonance images of breast cancer patients with tumor locations [Data set]. The Cancer Imaging Archive A Saha, MR Harowicz, LJ Grimm, J Weng, EH Cain, CE Kim, SV Ghate, ... Bethesda, MD, USA, 2021 | 12 | 2021 |
| Preoperative planning for structural heart disease MR Harowicz, A Shah, SL Zimmerman Radiologic Clinics 58 (4), 733-751, 2020 | 12 | 2020 |
| Deep learning-based features of breast MRI for prediction of occult invasive disease following a diagnosis of ductal carcinoma in situ: preliminary data Z Zhu, M Harowicz, J Zhang, A Saha, LJ Grimm, S Hwang, ... Medical imaging 2018: Computer-aided diagnosis 10575, 645-650, 2018 | 12 | 2018 |
| Breast cancer molecular subtype classification using deep features: preliminary results Z Zhu, E Albadawy, A Saha, J Zhang, MR Harowicz, MA Mazurowski Medical imaging 2018: Computer-aided diagnosis 10575, 651-656, 2018 | 10 | 2018 |
| Virtual lung screening trial (VLST): An in silico study inspired by the national lung screening trial for lung cancer detection FI Tushar, L Vancoillie, C McCabe, A Kavuri, L Dahal, B Harrawood, ... Medical Image Analysis 103, 103576, 2025 | 8 | 2025 |
| Kussmaul’s sign in pulmonary hypertension corresponds with severe pulmonary vascular pathology rather than right ventricular diastolic dysfunction FA Alkhunaizi, MR Harowicz, CG Ireland, BA Houston, RL Damico, ... Circulation: Heart Failure 14 (1), e007461, 2021 | 7 | 2021 |
| Ai in lung health: Benchmarking detection and diagnostic models across multiple ct scan datasets FI Tushar, A Wang, L Dahal, E Samei, MR Harowicz, J Kalpathy-Cramer, ... arXiv preprint arXiv:2405.04605, 2024 | 6 | 2024 |
| The Duke Lung Cancer Screening (DLCS) dataset: a reference dataset of annotated low-dose screening thoracic CT AJ Wang, FI Tushar, MR Harowicz, BC Tong, KJ Lafata, TD Tailor, JY Lo Radiology: Artificial Intelligence 7 (4), e240248, 2025 | 5 | 2025 |
Maciej A. MazurowskiAssociate Professor of Biostatistics & Bioinformatics, Radiology, Comp. Sci., ECE, Duke UniversityVerified email at duke.edu
