Mostafa Mehdipour Ghazi
Adjunkt
Pioneer AI (P1AI)
Øster Voldgade 3
1350 København K
- 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
- 2023
- Udgivet
Active Transfer Learning for 3D Hippocampus Segmentation
Wu, J., Kang, Z., 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, Z., 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
- 2022
- Udgivet
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
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Robust training of recurrent neural networks to handle missing data for disease progression modeling
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Robust parametric modeling of Alzheimer's disease progression
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