| Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI NM Braman, M Etesami, P Prasanna, C Dubchuk, H Gilmore, P Tiwari, ... Breast Cancer Research 19, 1-14, 2017 | 544 | 2017 |
| Predicting cancer outcomes with radiomics and artificial intelligence in radiology K Bera, N Braman, A Gupta, V Velcheti, A Madabhushi Nature reviews Clinical oncology 19 (2), 132-146, 2022 | 288 | 2022 |
| Perinodular and intranodular radiomic features on lung CT images distinguish adenocarcinomas from granulomas N Beig, M Khorrami, M Alilou, P Prasanna, N Braman, M Orooji, S Rakshit, ... Radiology 290 (3), 783-792, 2019 | 279 | 2019 |
| Association of peritumoral radiomics with tumor biology and pathologic response to preoperative targeted therapy for HER2 (ERBB2)–positive breast cancer N Braman, P Prasanna, J Whitney, S Singh, N Beig, M Etesami, ... JAMA network open 2 (4), e192561-e192561, 2019 | 233 | 2019 |
| Radiogenomic-based survival risk stratification of tumor habitat on Gd-T1w MRI is associated with biological processes in glioblastoma N Beig, K Bera, P Prasanna, J Antunes, R Correa, S Singh, ... Clinical Cancer Research 26 (8), 1866-1876, 2020 | 83 | 2020 |
| A deep learning classifier for prediction of pathological complete response to neoadjuvant chemotherapy from baseline breast DCE-MRI K Ravichandran, N Braman, A Janowczyk, A Madabhushi Medical imaging 2018: computer-aided diagnosis 10575, 79-88, 2018 | 69 | 2018 |
| Deep orthogonal fusion: multimodal prognostic biomarker discovery integrating radiology, pathology, genomic, and clinical data N Braman, JWH Gordon, ET Goossens, C Willis, MC Stumpe, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 59 | 2021 |
| Integrated, high-throughput, multiomics platform enables data-driven construction of cellular responses and reveals global drug mechanisms of action JL Norris, MA Farrow, DB Gutierrez, LD Palmer, N Muszynski, SD Sherrod, ... Journal of proteome research 16 (3), 1364-1375, 2017 | 42 | 2017 |
| Decision support for disease characterization and treatment response with disease and peri-disease radiomics A Madabhushi, M Orooji, M Rusu, P Linden, R Gilkeson, NM Braman US Patent 10,004,471, 2018 | 22 | 2018 |
| Radiomic features associated with HPV status on pretreatment computed tomography in oropharyngeal squamous cell carcinoma inform clinical prognosis B Song, K Yang, J Garneau, C Lu, L Li, J Lee, S Stock, NM Braman, ... Frontiers in oncology 11, 744250, 2021 | 21 | 2021 |
| Radiomics-based assessment of ultra-widefield leakage patterns and vessel network architecture in the PERMEATE study: insights into treatment durability P Prasanna, V Bobba, N Figueiredo, DD Sevgi, C Lu, N Braman, M Alilou, ... British Journal of Ophthalmology 105 (8), 1155-1160, 2021 | 21 | 2021 |
| Deep learning-based prediction of response to HER2-targeted neoadjuvant chemotherapy from pre-treatment dynamic breast MRI: a multi-institutional validation study N Braman, ME Adoui, M Vulchi, P Turk, M Etesami, P Fu, K Bera, S Drisis, ... arXiv preprint arXiv:2001.08570, 2020 | 18 | 2020 |
| Supervised machine learning in oncology: a clinician's guide N Murali, A Kucukkaya, A Petukhova, J Onofrey, J Chapiro Digestive disease interventions 4 (01), 073-081, 2020 | 17 | 2020 |
| Vascular network organization via hough transform (VaNgOGH): a novel radiomic biomarker for diagnosis and treatment response N Braman, P Prasanna, M Alilou, N Beig, A Madabhushi International Conference on Medical Image Computing and Computer-Assisted …, 2018 | 14 | 2018 |
| Disease detection in weakly annotated volumetric medical images using a convolutional LSTM network N Braman, D Beymer, E Dehghan arXiv preprint arXiv:1812.01087, 2018 | 12 | 2018 |
| Characterizing disease and treatment response with quantitative vessel tortuosity radiomics A Madabhushi, M Orooji, M Rusu, P Linden, R Gilkeson, NM Braman, ... US Patent 10,064,594, 2018 | 11 | 2018 |
| Development and external validation of a deep learning model for predicting response to HER2-targeted neoadjuvant therapy from pretreatment breast MRI. M Vulchi, M El Adoui, N Braman, P Turk, M Etesami, S Drisis, D Plecha, ... Journal of Clinical Oncology 37 (15_suppl), 593-593, 2019 | 10 | 2019 |
| Novel radiomic measurements of tumor-associated vasculature morphology on clinical imaging as a biomarker of treatment response in multiple cancers N Braman, P Prasanna, K Bera, M Alilou, M Khorrami, P Leo, M Etesami, ... Clinical Cancer Research 28 (20), 4410-4424, 2022 | 9 | 2022 |
| Response estimation through spatially oriented neural network and texture ensemble (RESONATE) JE Eben, N Braman, A Madabhushi International Conference on Medical Image Computing and Computer-Assisted …, 2019 | 9 | 2019 |
| Systems and methods for serial treatment of a muscular-skeletal deformity J Schoenecker, N Braman, A Houston, M Mendive, S Miao US Patent App. 15/275,690, 2017 | 6 | 2017 |
