| Automatic segmentation, classification, and follow‐up of optic pathway gliomas using deep learning and fuzzy c‐means clustering based on MRI M Artzi, S Gershov, L Ben‐Sira, J Roth, D Kozyrev, B Shofty, T Gazit, ... Medical Physics 47 (11), 5693-5701, 2020 | 23 | 2020 |
| Towards an autonomous clinical decision support system S Gershov, A Raz, E Karpas, S Laufer Engineering Applications of Artificial Intelligence 127, 107215, 2024 | 3 | 2024 |
| Automatic speech-based checklist for medical simulations S Gershov, Y Ringel, E Dvir, T Tsirilman, EB Zvi, S Braun, A Raz, S Laufer Proceedings of the Second Workshop on Natural Language Processing for …, 2021 | 3 | 2021 |
| Automating medical simulations S Gershov, D Braunold, R Spektor, A Ioscovich, A Raz, S Laufer Journal of Biomedical Informatics 144, 104446, 2023 | 2 | 2023 |
| CuVLER: Enhanced Unsupervised Object Discoveries through Exhaustive Self-Supervised Transformers S Arica, O Rubin, S Gershov, S Laufer Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | | 2024 |
| More Than Meets the Eye: Physicians’ Visual Attention in the Operating Room S Gershov, F Mahameed, A Raz, S Laufer International Workshop on Applications of Medical AI, 11-20, 2023 | | 2023 |
| More Than Meets the Eye: Analyzing Anesthesiologists’ Visual Attention in the Operating Room Using Deep Learning Models S Gershov, F Mahameed, A Raz, S Laufer International Workshop on PRedictive Intelligence In MEdicine, 253-264, 2023 | | 2023 |
| Modelling the resonant frequency associated with the spatio-temporal evolution of the bone-dental implant interface S Gershov, J Xie, FA Shah, K Shemtov-Yona, D Rittel Acta Biomaterialia 154, 302-311, 2022 | | 2022 |
| The Inherent Bias of Simulation-Based Assessment S Gershov, F Mahameed, A Raz, S Laufer Available at SSRN 4652511, 0 | | |
| Automating Clinical Simulations S Gershov, D Braunold, R Spector, A Ioscovich, A Raz, S Laufer Available at SSRN 4194672, 0 | | |
| Automatic segmentation and follow-up of optic pathway gliomas using deep learning and based on conventional MRI M Artzi, S Gershov, I Bressler, L Ben-Sira, S Constantini, T Gazit, ... | | |
Shlomi LauferTechnion在 technion.ac.il 的电子邮件经过验证
Shlomi LauferTechnion在 technion.ac.il 的电子邮件经过验证