| Machine learning for medical imaging BJ Erickson, P Korfiatis, Z Akkus, TL Kline radiographics 37 (2), 505-515, 2017 | 1761 | 2017 |
| An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction ZI Attia, PA Noseworthy, F Lopez-Jimenez, SJ Asirvatham, AJ Deshmukh, ... The Lancet 394 (10201), 861-867, 2019 | 1264 | 2019 |
| Deep learning for brain MRI segmentation: state of the art and future directions Z Akkus, A Galimzianova, A Hoogi, DL Rubin, BJ Erickson Journal of digital imaging 30, 449-459, 2017 | 1215 | 2017 |
| Association between pathological and MRI findings in multiple sclerosis M Filippi, W Brück, D Chard, F Fazekas, JJG Geurts, C Enzinger, ... The Lancet Neurology 18 (2), 198-210, 2019 | 711 | 2019 |
| Consensus recommendations for a standardized Brain Tumor Imaging Protocol in clinical trials BM Ellingson, M Bendszus, J Boxerman, D Barboriak, BJ Erickson, ... Neuro-oncology 17 (9), 1188-1198, 2015 | 711 | 2015 |
| Imaging classification of autosomal dominant polycystic kidney disease: a simple model for selecting patients for clinical trials MV Irazabal, LJ Rangel, EJ Bergstralh, SL Osborn, AJ Harmon, ... Journal of the American Society of Nephrology 26 (1), 160-172, 2015 | 673 | 2015 |
| Clinical and radiographic spectrum of pathologically confirmed tumefactive multiple sclerosis CF Lucchinetti, RH Gavrilova, I Metz, JE Parisi, BW Scheithauer, ... Brain 131 (7), 1759-1775, 2008 | 548 | 2008 |
| Association of maximal extent of resection of contrast-enhanced and noncontrast-enhanced tumor with survival within molecular subgroups of patients with newly diagnosed
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| The RSNA pediatric bone age machine learning challenge SS Halabi, LM Prevedello, J Kalpathy-Cramer, AB Mamonov, A Bilbily, ... Radiology 290 (2), 498-503, 2019 | 438 | 2019 |
| The effects of changes in utilization and technological advancements of cross-sectional imaging on radiologist workload RJ McDonald, KM Schwartz, LJ Eckel, FE Diehn, CH Hunt, BJ Bartholmai, ... Academic radiology 22 (9), 1191-1198, 2015 | 431 | 2015 |
| A roadmap for foundational research on artificial intelligence in medical imaging: from the 2018 NIH/RSNA/ACR/The Academy Workshop CP Langlotz, B Allen, BJ Erickson, J Kalpathy-Cramer, K Bigelow, ... Radiology 291 (3), 781-791, 2019 | 380 | 2019 |
| Initial clinical experience in MR imaging of the brain with a fast fluid-attenuated inversion-recovery pulse sequence. JN Rydberg, CA Hammond, RC Grimm, BJ Erickson, CR Jack Jr, ... Radiology 193 (1), 173-180, 1994 | 380 | 1994 |
| Automated abdominal segmentation of CT scans for body composition analysis using deep learning AD Weston, P Korfiatis, TL Kline, KA Philbrick, P Kostandy, T Sakinis, ... Radiology 290 (3), 669-679, 2019 | 330 | 2019 |
| Phase II trial of procarbazine, lomustine, and vincristine as initial therapy for patients with low-grade oligodendroglioma or oligoastrocytoma: efficacy and associations with
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| A survey of deep-learning applications in ultrasound: Artificial intelligencepowered ultrasound for improving clinical workflow Z Akkus, J Cai, A Boonrod, A Zeinoddini, AD Weston, KA Philbrick, ... Journal of the American College of Radiology 16 (9), 1318-1328, 2019 | 261 | 2019 |
| Predicting deletion of chromosomal arms 1p/19q in low-grade gliomas from MR images using machine intelligence Z Akkus, I Ali, J Sedlář, JP Agrawal, IF Parney, C Giannini, BJ Erickson Journal of digital imaging 30, 469-476, 2017 | 226 | 2017 |
| Toolkits and libraries for deep learning BJ Erickson, P Korfiatis, Z Akkus, T Kline, K Philbrick Journal of digital imaging 30, 400-405, 2017 | 218 | 2017 |
| Beneficial plasma exchange response in central nervous system inflammatory demyelination SM Magaña, BM Keegan, BG Weinshenker, BJ Erickson, SJ Pittock, ... Archives of Neurology 68 (7), 870-878, 2011 | 217 | 2011 |
| FLAIR histogram segmentation for measurement of leukoaraiosis volume CR Jack Jr, PC O'Brien, DW Rettman, MM Shiung, Y Xu, R Muthupillai, ... Journal of Magnetic Resonance Imaging: An Official Journal of the
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| Magicians corner: 9. Performance metrics for machine learning models BJ Erickson, F Kitamura Radiology: Artificial Intelligence 3 (3), e200126, 2021 | 209 | 2021 |
