Mostafa Mehdipour Ghazi
Assistant Professor
Pioneer AI (P1AI)
Øster Voldgade 3
1350 København K
- 2024
- 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, 2024, In: IEEE Transactions on Neural Networks and Learning Systems. 35, 1, p. 792-802Research output: Contribution to journal › Journal article › Research › peer-review
- Published
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, In: Frontiers in Aging Neuroscience. 16, 1345417.Research output: Contribution to journal › Journal article › Research › peer-review
- Published
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, p. 138-144 (Proceedings of Machine Learning Research, Vol. 233).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- 2023
- 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
- Published
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, p. 1-4 4 p. (Proceedings - International Symposium on Biomedical Imaging, Vol. 2023-April).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
GAN-ISI: Generative Adversarial Networks Image Source Identification Using Texture Analysis
Ghazi, M. M. & Mehdipour Ghazi, Mostafa, 2023, In: CEUR Workshop Proceedings. 3497, p. 1588-1595Research output: Contribution to journal › Conference article › Research › peer-review
- Published
Partial feedback online transfer learning with multi-source domains
Kang, Zhongfeng, Nielsen, Mads, Yang, B. & Mehdipour Ghazi, Mostafa, 2023, In: Information Fusion. 89, p. 29-40Research output: Contribution to journal › Journal article › Research › peer-review
- Published
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, In: GeroScience. 45, p. 1523–1538 16 p.Research output: Contribution to journal › Journal article › Research › peer-review
- 2022
- Published
- 2021
- 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
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 others, , 2021, In: Scientific Reports. 11, 1, 12 p., 3246.Research output: Contribution to journal › Journal article › 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
- 2019
- 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
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
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
- 2018
- Published
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 p.Research output: Contribution to conference › Paper › Research
ID: 204203641
Most downloads
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236
downloads
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 -
60
downloads
Robust training of recurrent neural networks to handle missing data for disease progression modeling
Research output: Contribution to conference › Paper › Research
Published -
53
downloads
Robust parametric modeling of Alzheimer's disease progression
Research output: Contribution to journal › Journal article › Research › peer-review
Published