| Machine learning fMRI classifier delineates subgroups of schizophrenia patients M Bleich-Cohen, S Jamshy, H Sharon, R Weizman, N Intrator, ... Schizophrenia research 160 (1-3), 196-200, 2014 | 59 | 2014 |
| Deep learning for distinguishing normal versus abnormal chest radiographs and generalization to two unseen diseases tuberculosis and COVID-19 Z Nabulsi, A Sellergren, S Jamshy, C Lau, E Santos, AP Kiraly, W Ye, ... Scientific reports 11 (1), 15523, 2021 | 39 | 2021 |
| Neural dynamics necessary and sufficient for transition into pre-sleep induced by EEG neurofeedback S Kinreich, I Podlipsky, S Jamshy, N Intrator, T Hendler Neuroimage 97, 19-28, 2014 | 37 | 2014 |
| Deep learning detection of active pulmonary tuberculosis at chest radiography matched the clinical performance of radiologists S Kazemzadeh, J Yu, S Jamshy, R Pilgrim, Z Nabulsi, C Chen, N Beladia, ... Radiology 306 (1), 124-137, 2023 | 25 | 2023 |
| Enhanced functional synchronization of medial and lateral PFC underlies internally-guided action planning K Rosenberg-Katz, S Jamshy, N Singer, I Podlipsky, S Kipervasser, ... Frontiers in Human Neuroscience 6, 2012 | 24 | 2012 |
| Similar image search for radiology K Eswaran, S Shetty, DSS Tse, S Jamshy, Z Ben-Haim US Patent 11,126,649, 2021 | 8 | 2021 |
| Searchlight Based Feature Extraction S Jamshy, O Perez, Y Yeshurun, T Hendler, N Intrator Machine Learning and Interpretation in Neuroimaging, 17-25, 2012 | 5 | 2012 |
| Deep learning for detecting pulmonary tuberculosis via chest radiography: an international study across 10 countries S Kazemzadeh, J Yu, S Jamshy, R Pilgrim, Z Nabulsi, C Chen, N Beladia, ... arXiv preprint arXiv:2105.07540, 2021 | 3 | 2021 |
| Reducing keypoint database size S Jamshy, E Krupka, Y Yeshurun Image Analysis and Processing–ICIAP 2009: 15th International Conference …, 2009 | 3 | 2009 |
| Determining Chest Conditions from Radiograph Data via Machine Learning S Kazemzadeh, DJ Yu, S Jamshy, R Pilgrim, ZI Nabulsi, AB Sellergren, ... US Patent App. 18/011,888, 2023 | | 2023 |
| Deep Learning for Distinguishing Normal versus Abnormal Chest Radiographs and Generalization to Unseen Diseases Z Nabulsi, A Sellergren, S Jamshy, C Lau, E Santos, AP Kiraly, W Ye, ... | | 2021 |
| Deep Learning for Distinguishing Normal versus Abnormal Chest Radiographs and Generalization to Unseen Diseases (preprint) Z Nabulsi, A Sellergren, S Jamshy, C Lau, E Santos, AP Kiraly, W Ye, ... | | 2020 |
| Factorized models HT Cheng, J Harmsen, AT Passos, DE Lluncor, S Jamshy, T Shaked, ... US Patent 10,102,482, 2018 | | 2018 |
| Local brain activity in the retrosplenial region probes our own prior experience O Perez, S Jamshy, A Talmor, N Intrator, Y Yeshurun, T Hendler JOURNAL OF MOLECULAR NEUROSCIENCE 51, S91-S91, 2013 | | 2013 |
| Local brain activity in the precuneous probes our own prior experience O Perez, S Jamshy, A Talmor, N Intrator, Y Yeshurun, T Hendler JOURNAL OF MOLECULAR NEUROSCIENCE 48, S90-S91, 2012 | | 2012 |
| Neural correlates of intentional emotions: combined intracranial EEG and fMRI study N Singer, I Podlipsky, F Esposito, S Jamshy, S Kipervasser, M Neufeld, ... Conference Abstract: XI International Conference on Cognitive Neuroscience …, 2011 | | 2011 |
| Keypoint Filtering Using Machine Learning S Jamshy University of Tel-Aviv, 2009 | | 2009 |
Nathan IntratorProfessor of Computer Science and Neuroscience, Tel Aviv UniversityVerified email at post.tau.ac.il
