Mostafa Mehdipour Ghazi
Adjunkt
Pioneer AI (P1AI)
Øster Voldgade 3
1350 København K
- Udgivet
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. (red.). Springer VS, s. 275-286 12 s. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bind 11953 LNCS).Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
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, I: NeuroImage. 225, 12 s., 117460.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
- Udgivet
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 s.Publikation: Konferencebidrag › Konferenceabstrakt til konference › Forskning
- Udgivet
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 s.Publikation: Working paper › Preprint › Forskning
- Udgivet
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, I: Medical Image Analysis. 53, s. 39-46Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
- Udgivet
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. (red.). Springer, s. 224-234 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bind 14307 LNCS).Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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Robust training of recurrent neural networks to handle missing data for disease progression modeling
Publikation: Konferencebidrag › Paper › Forskning
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Robust parametric modeling of Alzheimer's disease progression
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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