| InceptionGCN: receptive field aware graph convolutional network for disease prediction A Kazi, S Shekarforoush, S Arvind Krishna, H Burwinkel, G Vivar, ... Information Processing in Medical Imaging: 26th International Conference …, 2019 | 158 | 2019 |
| Differentiable graph module (dgm) for graph convolutional networks A Kazi, L Cosmo, SA Ahmadi, N Navab, MM Bronstein IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (2), 1606-1617, 2022 | 141 | 2022 |
| Latent-graph learning for disease prediction L Cosmo, A Kazi, SA Ahmadi, N Navab, M Bronstein Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 72 | 2020 |
| RA-GCN: Graph convolutional network for disease prediction problems with imbalanced data M Ghorbani, A Kazi, MS Baghshah, HR Rabiee, N Navab Medical image analysis 75, 102272, 2022 | 60 | 2022 |
| Graph convolution based attention model for personalized disease prediction A Kazi, S Shekarforoush, S Arvind Krishna, H Burwinkel, G Vivar, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 45 | 2019 |
| Self-attention equipped graph convolutions for disease prediction A Kazi, S Shekarforoush, K Kortuem, S Albarqouni, N Navab 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019 …, 2019 | 44 | 2019 |
| Precise proximal femur fracture classification for interactive training and surgical planning A Jiménez-Sánchez, A Kazi, S Albarqouni, C Kirchhoff, P Biberthaler, ... International journal of computer assisted radiology and surgery 15, 847-857, 2020 | 42* | 2020 |
| Automatic classification of proximal femur fractures based on attention models A Kazi, S Albarqouni, AJ Sanchez, S Kirchhoff, P Biberthaler, N Navab, ... Machine Learning in Medical Imaging: 8th International Workshop, MLMI 2017 …, 2017 | 34 | 2017 |
| Metric hashing forests S Conjeti, A Katouzian, A Kazi, S Mesbah, D Beymer, ... Medical image analysis 34, 13-29, 2016 | 23 | 2016 |
| Latent patient network learning for automatic diagnosis L Cosmo, A Kazi, SA Ahmadi, N Navab, M Bronstein arXiv preprint arXiv:2003.13620, 77, 2020 | 22 | 2020 |
| Latent graph inference using product manifolds HS de Ocáriz Borde, A Kazi, F Barbero, P Lio The Eleventh International Conference on Learning Representations, 2023 | 16 | 2023 |
| Simultaneous imputation and classification using Multigraph Geometric Matrix Completion (MGMC): Application to neurodegenerative disease classification G Vivar, A Kazi, H Burwinkel, A Zwergal, N Navab, SA Ahmadi Artificial intelligence in medicine 117, 102097, 2021 | 15 | 2021 |
| Weakly-supervised localization and classification of proximal femur fractures A Jiménez-Sánchez, A Kazi, S Albarqouni, S Kirchhoff, A Sträter, ... arXiv preprint arXiv:1809.10692, 2018 | 15 | 2018 |
| Adaptive image-feature learning for disease classification using inductive graph networks H Burwinkel, A Kazi, G Vivar, S Albarqouni, G Zahnd, N Navab, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 14 | 2019 |
| Simultaneous imputation and disease classification in incomplete medical datasets using Multigraph Geometric Matrix Completion (MGMC) G Vivar, A Kazi, H Burwinkel, A Zwergal, N Navab, SA Ahmadi arXiv preprint arXiv:2005.06935, 2020 | 13 | 2020 |
| Endorsing cellular competitiveness in aberrant epithelium of oral submucous fibrosis progression: neighbourhood analysis of immunohistochemical attributes A Anura, A Kazi, M Pal, RR Paul, S Sengupta, J Chatterjee Histochemistry and Cell Biology 150, 61-75, 2018 | 13 | 2018 |
| Ia-gcn: Interpretable attention based graph convolutional network for disease prediction A Kazi, S Farghadani, I Aganj, N Navab International Workshop on Machine Learning in Medical Imaging, 382-392, 2023 | 9 | 2023 |
| Gkd: Semi-supervised graph knowledge distillation for graph-independent inference M Ghorbani, M Bahrami, A Kazi, M Soleymani Baghshah, HR Rabiee, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 9 | 2021 |
| Multi-modal graph fusion for inductive disease classification in incomplete datasets G Vivar, H Burwinkel, A Kazi, A Zwergal, N Navab, SA Ahmadi arXiv preprint arXiv:1905.03053, 2019 | 8 | 2019 |
| Unsupervised pre-training of graph transformers on patient population graphs C Pellegrini, N Navab, A Kazi Medical Image Analysis 89, 102895, 2023 | 7 | 2023 |
Nassir NavabProfessor of Computer Science, Technische Universität München在 cs.tum.edu 的电子邮件经过验证
