Mostafa Mehdipour Ghazi
Adjunkt
Pioneer AI (P1AI)
Øster Voldgade 3
1350 København K
- 2018
- Udgivet
Robust training of recurrent neural networks to handle missing data for disease progression modeling
Mehdipour Ghazi, Mostafa, Nielsen, Mads, Pai, A. S. U., Cardoso, M. J., Modat, M., Ourselin, S. & Sørensen, L., 2018. 9 s.Publikation: Konferencebidrag › Paper › Forskning
- 2019
- 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
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
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
- 2021
- 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
- Udgivet
Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients
Jimenez-Solem, E., Petersen, T. S., Hansen, C., Hansen, C., Lioma, C., Igel, C., Boomsma, W., Krause, O., Lorenzen, S., Selvan, R., Petersen, J., Nyeland, M. E., Ankarfeldt, M. Z., Virenfeldt, G. M., Winther-Jensen, M., Linneberg, A., Ghazi, M. M., Detlefsen, N., Lauritzen, A. D., Smith, A. G. & 15 flere, , 2021, I: Scientific Reports. 11, 1, 12 s., 3246.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › 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
- 2022
- Udgivet
- 2023
- 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
- Udgivet
Deep Learning-Based Assessment of Cerebral Microbleeds in COVID-19
Ferrer, N. R., Vendela Sagar, M., Klein, Kiril Vadimovic, Kruuse, Christina Rostrup, Nielsen, Mads & Mehdipour Ghazi, Mostafa, 2023, 2023 IEEE International Symposium on Biomedical Imaging, ISBI 2023. IEEE Computer Society Press, s. 1-4 4 s. (Proceedings - International Symposium on Biomedical Imaging, Bind 2023-April).Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
- Udgivet
GAN-ISI: Generative Adversarial Networks Image Source Identification Using Texture Analysis
Ghazi, M. M. & Mehdipour Ghazi, Mostafa, 2023, I: CEUR Workshop Proceedings. 3497, s. 1588-1595Publikation: Bidrag til tidsskrift › Konferenceartikel › Forskning › fagfællebedømt
- Udgivet
Partial feedback online transfer learning with multi-source domains
Kang, Zhongfeng, Nielsen, Mads, Yang, B. & Mehdipour Ghazi, Mostafa, 2023, I: Information Fusion. 89, s. 29-40Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
- Udgivet
Power and distribution of evoked gamma oscillations in brain aging and cognitive performance
Bakhtiari, Aftab, Petersen, J., Urdanibia-Centelles, O., Mehdipour Ghazi, Mostafa, Fagerlund, Birgitte, Mortensen, Erik Lykke, Osler, Merete, Lauritzen, Martin & Benedek, Krisztina, 2023, I: GeroScience. 45, s. 1523–1538 16 s.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
- 2024
- 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, 2024, I: IEEE Transactions on Neural Networks and Learning Systems. 35, 1, s. 792-802Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
- Udgivet
COVID-19-associated cerebral microbleeds in the general population
Sagar, M. V., Ferrer, N. R., Mehdipour Ghazi, Mostafa, Klein, Kiril Vadimovic, Solem, Espen Victor Jimenez, Nielsen, Mads & Kruuse, Christina Rostrup, 2024, I: Brain Communications. 6, 3, fcae127.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
- Udgivet
Comparative analysis of multimodal biomarkers for amyloid-beta positivity detection in Alzheimer's disease cohorts
Mehdipour Ghazi, Mostafa, Selnes, P., Timón-Reina, S., Tecelão, S., Ingala, S., Bjørnerud, A., Kirsebom, B. E., Fladby, T. & Nielsen, Mads, 2024, I: Frontiers in Aging Neuroscience. 16, 1345417.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
- Udgivet
Heterogeneous Learning for Brain Lesion Segmentation, Detection, and Classification
Llambias, Sebastian Nørgaard, Nielsen, Mads & Mehdipour Ghazi, Mostafa, 2024, Proceedings of the 5th Northern Lights Deep Learning Conference ({NLDL}). PMLR, s. 138-144 (Proceedings of Machine Learning Research, Bind 233).Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
ID: 204203641
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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
Udgivet -
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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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