Mostafa Mehdipour Ghazi
Assistant Professor
Pioneer AI (P1AI)
Øster Voldgade 3
1350 København K
- Published
On the initialization of long short-term memory networks
Mehdipour Ghazi, Mostafa, Nielsen, Mads, Pai, A., Modat, M., Cardoso, M. J., Ourselin, S. & Sørensen, L., 2019, Neural Information Processing - 26th International Conference, ICONIP 2019, Proceedings. Gedeon, T., Wong, K. W. & Lee, M. (eds.). Springer VS, p. 275-286 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 11953 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
Robust parametric modeling of Alzheimer's disease progression
Mehdipour Ghazi, Mostafa, Nielsen, Mads, Pai, A., Modat, M., Jorge Cardoso, M., Ourselin, S. & Sørensen, L., 2021, In: NeuroImage. 225, 12 p., 117460.Research output: Contribution to journal › Journal article › Research › peer-review
- Published
MRI Biomarkers Improve Disease Progression Modeling-Based Prediction of Cognitive Decline
Mehdipour Ghazi, Mostafa, Nielsen, Mads, Pai, A. S. U., Modat , M., Cardoso , J., Ourselin, S. & Sorensen, L., 2019. 1 p.Research output: Contribution to conference › Conference abstract for conference › Research
- Published
CARRNN: A Continuous Autoregressive Recurrent Neural Network for Deep Representation Learning from Sporadic Temporal Data
Mehdipour Ghazi, Mostafa, Sørensen, L., Ourselin, S. & Nielsen, Mads, 2021, arXiv.org, 11 p.Research output: Working paper › Preprint › Research
- Published
Training recurrent neural networks robust to incomplete data: application to Alzheimer’s disease progression modeling
Mehdipour Ghazi, Mostafa, Nielsen, Mads, Pai, A. S. U., Cardoso, M. J., Modat, M., Ourselin, S. & Sørensen, L., 2019, In: Medical Image Analysis. 53, p. 39-46Research output: Contribution to journal › Journal article › Research › peer-review
- Published
Active Transfer Learning for 3D Hippocampus Segmentation
Wu, J., Kang, Zhongfeng, Llambias, Sebastian Nørgaard, Mehdipour Ghazi, Mostafa & Nielsen, Mads, 2023, Medical Image Learning with Limited and Noisy Data - 2nd International Workshop, MILLanD 2023, Held in Conjunction with MICCAI 2023, Proceedings. Xue, Z., Antani, S., Zamzmi, G., Yang, F., Rajaraman, S., Liang, Z., Huang, S. X. & Linguraru, M. G. (eds.). Springer, p. 224-234 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 14307 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
ID: 204203641
Most downloads
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240
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Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients
Research output: Contribution to journal › Journal article › Research › peer-review
Published -
61
downloads
Robust training of recurrent neural networks to handle missing data for disease progression modeling
Research output: Contribution to conference › Paper › Research
Published -
54
downloads
Robust parametric modeling of Alzheimer's disease progression
Research output: Contribution to journal › Journal article › Research › peer-review
Published