| Up-regulation of cerebral cytochrome-c-oxidase and hemodynamics by transcranial infrared laser stimulation: a broadband near-infrared spectroscopy study X Wang, F Tian, DD Reddy, SS Nalawade, DW Barrett, F Gonzalez-Lima, ... Journal of Cerebral Blood Flow & Metabolism 37 (12), 3789-3802, 2017 | 175 | 2017 |
| Retracted: A novel fully automated MRI-based deep-learning method for classification of IDH mutation status in brain gliomas CG Bangalore Yogananda, BR Shah, M Vejdani-Jahromi, SS Nalawade, ... Neuro-oncology 22 (3), 402-411, 2020 | 151 | 2020 |
| MRI-based deep-learning method for determining glioma MGMT promoter methylation status CGB Yogananda, BR Shah, SS Nalawade, GK Murugesan, FF Yu, ... American Journal of Neuroradiology 42 (5), 845-852, 2021 | 86 | 2021 |
| A fully automated deep learning network for brain tumor segmentation CGB Yogananda, BR Shah, M Vejdani-Jahromi, SS Nalawade, ... Tomography 6 (2), 186-193, 2020 | 73 | 2020 |
| Impact of heat on metabolic and hemodynamic changes in transcranial infrared laser stimulation measured by broadband near-infrared spectroscopy X Wang, DD Reddy, SS Nalawade, S Pal, F Gonzalez-Lima, H Liu Neurophotonics 5 (1), 011004-011004, 2018 | 72 | 2018 |
| A novel fully automated MRI-based deep-learning method for classification of 1p/19q co-deletion status in brain gliomas CGB Yogananda, BR Shah, FF Yu, MC Pinho, SS Nalawade, ... Neuro-oncology advances 2 (Supplement_4), iv42-iv48, 2020 | 55 | 2020 |
| Federated benchmarking of medical artificial intelligence with MedPerf A Karargyris, R Umeton, MJ Sheller, A Aristizabal, J George, A Wuest, ... Nature machine intelligence 5 (7), 799-810, 2023 | 49 | 2023 |
| QU-BraTS: MICCAI BraTS 2020 challenge on quantifying uncertainty in brain tumor segmentation-analysis of ranking scores and benchmarking results R Mehta, A Filos, U Baid, C Sako, R McKinley, M Rebsamen, K Dätwyler, ... The journal of machine learning for biomedical imaging 2022, 2022 | 43 | 2022 |
| Classification of brain tumor isocitrate dehydrogenase status using MRI and deep learning S Nalawade, GK Murugesan, M Vejdani-Jahromi, RA Fisicaro, ... Journal of Medical Imaging 6 (4), 046003-046003, 2019 | 28 | 2019 |
| Biomedical image analysis competitions: The state of current participation practice M Eisenmann, A Reinke, V Weru, MD Tizabi, F Isensee, TJ Adler, ... arXiv preprint arXiv:2212.08568, 2022 | 25 | 2022 |
| Fully automated brain tumor segmentation and survival prediction of gliomas using deep learning and MRI CG Bangalore Yogananda, B Wagner, SS Nalawade, GK Murugesan, ... International MICCAI Brainlesion Workshop, 99-112, 2020 | 21 | 2020 |
| Multidimensional and multiresolution ensemble networks for brain tumor segmentation GK Murugesan, S Nalawade, C Ganesh, B Wagner, FF Yu, B Fei, ... Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2020 | 20 | 2020 |
| BrainNET: Inference of brain network topology using machine learning GK Murugesan, C Ganesh, S Nalawade, EM Davenport, B Wagner, ... Brain connectivity 10 (8), 422-435, 2020 | 12 | 2020 |
| Federated Learning for Brain Tumor Segmentation Using MRI and Transformers SS Nalawade, CGB Yogananda, B Wagner, D Reddy, Y Das, FF Yu, B Fei, ... International MICCAI Brainlesion Workshop 1296, 444–454, 2022 | 8 | 2022 |
| Disparity autoencoders for multi-class brain tumor segmentation CG Bangalore Yogananda, Y Das, BC Wagner, SS Nalawade, D Reddy, ... International MICCAI Brainlesion Workshop, 116-124, 2021 | 8 | 2021 |
| Impact of heat on metabolic and hemodynamic changes in transcranial infrared laser stimulation measured by broadband near-infrared spectroscopy. Neurophotonics 5, 011004 X Wang, DD Reddy, SS Nalawade, S Pal, F Gonzalez-Lima, H Liu | 7 | 2017 |
| A radiomic machine learning model to predict treatment response to methotrexate and survival outcomes in primary central nervous system lymphoma (pcnsl) OM Ali, SS Nalawade, Y Xi, B Wagner, A Mazal, S Ahlers, SM Rizvi, ... Blood 136, 29-30, 2020 | 4 | 2020 |
| Brain tumor IDH, 1p/19q, and MGMT molecular classification using MRI-based deep learning: an initial study on the effect of motion and motion correction SS Nalawade, FF Yu, CG Bangalore Yogananda, GK Murugesan, ... Journal of Medical Imaging 9 (1), 016001-016001, 2022 | 3 | 2022 |
| Classification of brain tumor IDH status using MRI and deep learning. bioRxiv. 2019; 757344 S Nalawade, G Murugesan, M Vejdani-Jahromi, RA Fisicaro, ... | 3* | |
| Brain Tumor IDH, 1p/19q, and MGMT molecular classification using MRI-based deep learning: effect of motion and motion correction SS Nalawade, FF Yu, CG Bangalore Yogananda, GK Murugesan, ... bioRxiv, 2020.06. 01.126375, 2020 | 2 | 2020 |