| Imaging patterns predict patient survival and molecular subtype in glioblastoma via machine learning techniques L Macyszyn, H Akbari, JM Pisapia, X Da, M Attiah, V Pigrish, Y Bi, S Pal, ... Neuro-oncology 18 (3), 417-425, 2015 | 308 | 2015 |
| Imaging surrogates of infiltration obtained via multiparametric imaging pattern analysis predict subsequent location of recurrence of glioblastoma H Akbari, L Macyszyn, X Da, M Bilello, RL Wolf, M Martinez-Lage, G Biros, ... Neurosurgery 78 (4), 572-580, 2016 | 150 | 2016 |
| Pattern analysis of dynamic susceptibility contrast-enhanced MR imaging demonstrates peritumoral tissue heterogeneity H Akbari, L Macyszyn, X Da, RL Wolf, M Bilello, R Verma, DM O’Rourke, ... Radiology 273 (2), 502-510, 2014 | 103 | 2014 |
| Direct versus indirect revascularization procedures for moyamoya disease: a comparative effectiveness study L Macyszyn, M Attiah, TS Ma, Z Ali, R Faught, A Hossain, K Man, H Patel, ... Journal of neurosurgery 126 (5), 1523-1529, 2017 | 82 | 2017 |
| Isoform-level gene signature improves prognostic stratification and accurately classifies glioblastoma subtypes S Pal, Y Bi, L Macyszyn, LC Showe, DM O'Rourke, RV Davuluri Nucleic acids research 42 (8), e64-e64, 2014 | 73 | 2014 |
| Automated tumor volumetry using computer-aided image segmentation B Gaonkar, L Macyszyn, M Bilello, MS Sadaghiani, H Akbari, MA Attiah, ... Academic radiology 22 (5), 653-661, 2015 | 50 | 2015 |
| Individualized map of white matter pathways: connectivity-based paradigm for neurosurgical planning B Tunç, M Ingalhalikar, D Parker, J Lecoeur, N Singh, RL Wolf, ... Neurosurgery 79 (4), 568-577, 2016 | 43 | 2016 |
| Deep learning in the small sample size setting: cascaded feed forward neural networks for medical image segmentation B Gaonkar, D Hovda, N Martin, L Macyszyn Medical Imaging 2016: Computer-Aided Diagnosis 9785, 646-653, 2016 | 41 | 2016 |
| Multi-parameter ensemble learning for automated vertebral body segmentation in heterogeneously acquired clinical MR images B Gaonkar, Y Xia, DS Villaroman, A Ko, M Attiah, JS Beckett, L Macyszyn IEEE journal of translational engineering in health and medicine 5, 1-12, 2017 | 34 | 2017 |
| Relating quality of life to Glasgow outcome scale health states J Kosty, L Macyszyn, K Lai, J McCroskery, HR Park, SC Stein Journal of neurotrauma 29 (7), 1322-1327, 2012 | 33 | 2012 |
| Updated external validation of the SORG machine learning algorithms for prediction of ninety-day and one-year mortality after surgery for spinal metastasis AA Shah, AV Karhade, HY Park, WL Sheppard, LJ Macyszyn, RG Everson, ... The Spine Journal 21 (10), 1679-1686, 2021 | 31 | 2021 |
| Navigated odontoid screw placement using the O-arm: technical note and case series JM Pisapia, NR Nayak, RD Salinas, L Macyszyn, JYK Lee, TH Lucas, ... Journal of Neurosurgery: Spine 26 (1), 10-18, 2017 | 31 | 2017 |
| Natural history of the aging spine: a cross-sectional analysis of spinopelvic parameters in the asymptomatic population M Attiah, B Gaonkar, Y Alkhalid, D Villaroman, R Medina, C Ahn, T Niu, ... Journal of Neurosurgery: Spine 32 (1), 63-68, 2019 | 30 | 2019 |
| A deep learning approach to spine segmentation using a feed-forward chain of pixel-wise convolutional networks W Whitehead, S Moran, B Gaonkar, L Macyszyn, S Iyer 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018 | 30 | 2018 |
| United States Medical Licensing Examination Step 1 scores directly correlate with American Board of Neurological Surgery scores: a single-institution experience DT Nagasawa, JS Beckett, C Lagman, LK Chung, B Schmidt, M Safaee, ... World Neurosurgery 98, 427-431, 2017 | 29 | 2017 |
| Quantitative analysis of spinal canal areas in the lumbar spine: an imaging informatics and machine learning study B Gaonkar, D Villaroman, J Beckett, C Ahn, M Attiah, D Babayan, ... American Journal of Neuroradiology 40 (9), 1586-1591, 2019 | 26 | 2019 |
| Quantitative analysis of neural foramina in the lumbar spine: an imaging informatics and machine learning study B Gaonkar, J Beckett, D Villaroman, C Ahn, M Edwards, S Moran, M Attiah, ... Radiology: Artificial Intelligence 1 (2), 180037, 2019 | 22 | 2019 |
| Predicting spinal surgery candidacy from imaging data using machine learning B Wilson, B Gaonkar, B Yoo, B Salehi, M Attiah, D Villaroman, C Ahn, ... Neurosurgery 89 (1), 116-121, 2021 | 20 | 2021 |
| Ethical issues arising due to bias in training AI algorithms in healthcare and data sharing as a potential solution B Gaonkar, K Cook, L Macyszyn The AI Ethics Journal 1 (1), 2020 | 20 | 2020 |
| Amyloid-β–related angiitis: a report of 2 cases with unusual presentations DW Ng, S Magaki, KH Terashima, AM Keener, N Salamon, S Karnezis, ... Human Pathology 64, 191-197, 2017 | 20 | 2017 |
