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2025 Journal Article BayTTA: Uncertainty-aware medical image classification with optimized test-time augmentation using Bayesian model averagingSherkatghanad, Zeinab, Abdar, Moloud, Bakhtyari, Mohammadreza, Pławiak, Paweł and Makarenkov, Vladimir (2025). BayTTA: Uncertainty-aware medical image classification with optimized test-time augmentation using Bayesian model averaging. Knowledge-Based Systems, 327 114123, 114123-327. doi: 10.1016/j.knosys.2025.114123 |
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2025 Journal Article Survey on Leveraging Uncertainty Estimation Towards Trustworthy Deep Neural Networks: The Case of Reject Option and Post-training ProcessingHasan, Md Mehedi, Abdar, Moloud, Khosravi, Abbas, Aickelin, Uwe, Lio, Pietro, Hossain, Ibrahim, Rahman, Ashikur and Nahavandi, Saeid (2025). Survey on Leveraging Uncertainty Estimation Towards Trustworthy Deep Neural Networks: The Case of Reject Option and Post-training Processing. ACM Computing Surveys, 57 (9) 236, 1-35. doi: 10.1145/3727633 |
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2025 Journal Article Attention-guided hierarchical fusion U-Net for uncertainty-driven medical image segmentationMunia, Afsana Ahmed, Abdar, Moloud, Hasan, Mehedi, Jalali, Mohammad S., Banerjee, Biplab, Khosravi, Abbas, Hossain, Ibrahim, Fu, Huazhu and Frangi, Alejandro F. (2025). Attention-guided hierarchical fusion U-Net for uncertainty-driven medical image segmentation. Information Fusion, 115 102719. doi: 10.1016/j.inffus.2024.102719 |
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2025 Journal Article It is time to reassess reporting of electroconvulsive therapy data in New Zealand: A 17-year retrospective analysis of treatment data from WaikatoLundin, Robert M, Kannangara, Savani, Jenkins, Matthew, Carroll, Teresa, Wakefield, Kathrine, Patrick, Colin, Abdar, Moloud, Khosravi, Abbas, Loo, Colleen and Berk, Michael (2025). It is time to reassess reporting of electroconvulsive therapy data in New Zealand: A 17-year retrospective analysis of treatment data from Waikato. Australian and New Zealand Journal of Psychiatry, 59 (5), 423-432. doi: 10.1177/00048674251324795 |
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2025 Conference Publication Machine learning in electroconvulsive therapyLundin, Robert, Abdar, Moloud, Khosravi, Abbas, Loo, Colleen and Berk, Michael (2025). Machine learning in electroconvulsive therapy. 6th International Brain Stimulation Meeting, Kobe, Japan, 23–26 February 2025. Philadelphia, PA United States: Elsevier. doi: 10.1016/j.brs.2024.12.395 |
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2024 Conference Publication Can commonsense knowledge improve CLIP's performance in cross-domain VQA?N. C., Mohamad Hassan, Jha, Ankit, Abdar, Moloud and Banerjee, Biplab (2024). Can commonsense knowledge improve CLIP's performance in cross-domain VQA?. ICVGIP 2024: Indian Conference on Computer Vision Graphics and Image Processing, Bengaluru, Karnataka, India, 13-15 December 2024. New York, United States: Association for Computing Machinery. doi: 10.1145/3702250.3702265 |
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2024 Journal Article Machine learning in electroconvulsive therapy a systematic reviewLundin, Robert M., Falcao, Veronica Podence, Kannangara, Savani, Eakin, Charles W., Abdar, Moloud, O'Neill, John, Khosravi, Abbas, Eyre, Harris, Nahavandi, Saeid, Loo, Colleen and Berk, Michael (2024). Machine learning in electroconvulsive therapy a systematic review. Journal of ECT, 40 (4), 245-253. doi: 10.1097/YCT.0000000000001009 |
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2024 Journal Article UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional dataAhadzadeh, Behrouz, Abdar, Moloud, Foroumandi, Mahdieh, Safara, Fatemeh, Khosravi, Abbas, García, Salvador and Suganthan, Ponnuthurai Nagaratnam (2024). UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data. Swarm and Evolutionary Computation, 91 101715, 101715. doi: 10.1016/j.swevo.2024.101715 |
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2024 Journal Article Handling of uncertainty in medical data using machine learning and probability theory techniques: a review of 30 years (1991–2020)Alizadehsani, Roohallah, Roshanzamir, Mohamad, Hussain, Sadiq, Khosravi, Abbas, Koohestani, Afsaneh, Zangooei, Mohammad Hossein, Abdar, Moloud, Beykikhoshk, Adham, Shoeibi, Afshin, Zare, Assef, Panahiazar, Maryam, Nahavandi, Saeid, Srinivasan, Dipti, Atiya, Amir F. and Acharya, U. Rajendra (2024). Handling of uncertainty in medical data using machine learning and probability theory techniques: a review of 30 years (1991–2020). Annals of Operations Research, 339 (3), 1077-1118. doi: 10.1007/s10479-021-04006-2 |
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2024 Conference Publication Unknown prompt, the only lacuna: unveiling CLIP's potential for open domain generalizationSingha, Mainak, Jha, Ankit, Bose, Shirsha, Nair, Ashwin, Abdar, Moloud and Banerjee, Biplab (2024). Unknown prompt, the only lacuna: unveiling CLIP's potential for open domain generalization. 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, United States, 16-22 June 2024. Washington, DC, United States: IEEE Computer Society. doi: 10.1109/CVPR52733.2024.01264 |
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2024 Journal Article A review of deep learning for video captioningAbdar, Moloud, Kollati, Meenakshi, Kuraparthi, Swaraja, Pourpanah, Farhad, McDuff, Daniel, Ghavamzadeh, Mohammad, Yan, Shuicheng, Mohamed, Abduallah, Khosravi, Abbas, Cambria, Erik and Porikli, Fatih (2024). A review of deep learning for video captioning. IEEE Transactions on Pattern Analysis and Machine Intelligence. doi: 10.1109/tpami.2024.3522295 |
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2024 Journal Article Improved binary differential evolution with dimensionality reduction mechanism and binary stochastic search for feature selectionAhadzadeh, Behrouz, Abdar, Moloud, Safara, Fatemeh, Aghaei, Leyla, Mirjalili, Seyedali, Khosravi, Abbas, Garcia, Salvador, Karray, Fakhri and Acharya, U. Rajendra (2024). Improved binary differential evolution with dimensionality reduction mechanism and binary stochastic search for feature selection. Applied Soft Computing, 151 111141, 1-26. doi: 10.1016/j.asoc.2023.111141 |
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2023 Journal Article SpinalNet: deep neural network with gradual inputKabir, H. M. Dipu, Abdar, Moloud, Khosravi, Abbas, Jalali, Seyed Mohammad Jafar, Atiya, Amir F., Nahavandi, Saeid and Srinivasan, Dipti (2023). SpinalNet: deep neural network with gradual input. IEEE Transactions on Artificial Intelligence, 4 (5), 1165-1177. doi: 10.1109/tai.2022.3185179 |
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2023 Journal Article Binarized multi-gate mixture of Bayesian experts for cardiac syndrome X diagnosis: a clinician-in-the-loop scenario with a belief-uncertainty fusion paradigmAbdar, Moloud, Mehrzadi, Arash, Goudarzi, Milad, Masoudkabir, Farzad, Rundo, Leonardo, Mamouei, Mohammad, Sala, Evis, Khosravi, Abbas, Makarenkov, Vladimir, Acharya, U. Rajendra, Saadatagah, Seyedmohammad, Naderian, Mohammadreza, Garcia, Salvador, Sarrafzadegan, Nizal and Nahavandi, Saeid (2023). Binarized multi-gate mixture of Bayesian experts for cardiac syndrome X diagnosis: a clinician-in-the-loop scenario with a belief-uncertainty fusion paradigm. Information Fusion, 97 101813, 1-20. doi: 10.1016/j.inffus.2023.101813 |
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2023 Journal Article An optimal nonlinear model predictive control-based motion cueing algorithm using cascade optimization and human interactionQazani, Mohammad Reza Chalak, Asadi, Houshyar, Chen, Yutao, Abdar, Moloud, Karkoub, Mansour, Mohamed, Shady, Lim, Chee Peng and Nahavandi, Saeid (2023). An optimal nonlinear model predictive control-based motion cueing algorithm using cascade optimization and human interaction. IEEE Transactions on Intelligent Transportation Systems, 24 (9), 9191-9202. doi: 10.1109/TITS.2023.3271361 |
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2023 Journal Article Using traditional machine learning and deep learning methods for on- and off-target prediction in CRISPR/Cas9: a reviewSherkatghanad, Zeinab, Abdar, Moloud, Charlier, Jeremy and Makarenkov, Vladimir (2023). Using traditional machine learning and deep learning methods for on- and off-target prediction in CRISPR/Cas9: a review. Briefings in Bioinformatics, 24 (3) bbad131, 1-25. doi: 10.1093/bib/bbad131 |
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2023 Journal Article Synthetic Datasets for Numeric Uncertainty Quantification: Proposing Datasets for Future ResearchersKabir, H M Dipu, Abdar, Moloud, Khosravi, Abbas, Nahavandi, Darius, Mondal, Subrota Kumar, Khanam, Sadia, Mohamed, Shady, Srinivasan, Dipti, Nahavandi, Saeid and Suganthan, Ponnuthurai Nagaratnam (2023). Synthetic Datasets for Numeric Uncertainty Quantification: Proposing Datasets for Future Researchers. IEEE Systems, Man, and Cybernetics Magazine, 9 (2), 39-48. doi: 10.1109/msmc.2022.3218423 |
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2023 Journal Article Toxicity prediction in pelvic radiotherapy using multiple instance learning and cascaded attention layersElhaminia, Behnaz, Gilbert, Alexandra, Lilley, John, Abdar, Moloud, Frangi, Alejandro F., Scarsbrook, Andrew, Appelt, Ane and Gooya, Ali (2023). Toxicity prediction in pelvic radiotherapy using multiple instance learning and cascaded attention layers. IEEE Journal of Biomedical and Health Informatics, 27 (4), 1958-1966. doi: 10.1109/jbhi.2023.3238825 |
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2023 Journal Article Quantum face recognition protocol with ghost imagingSalari, Vahid, Paneru, Dilip, Saglamyurek, Erhan, Ghadimi, Milad, Abdar, Moloud, Rezaee, Mohammadreza, Aslani, Mehdi, Barzanjeh, Shabir and Karimi, Ebrahim (2023). Quantum face recognition protocol with ghost imaging. Scientific Reports, 13 (1) 2401, 1-9. doi: 10.1038/s41598-022-25280-5 |
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2023 Journal Article UncertaintyFuseNet: Robust uncertainty-aware hierarchical feature fusion model with Ensemble Monte Carlo Dropout for COVID-19 detectionAbdar, Moloud, Salari, Soorena, Qahremani, Sina, Lam, Hak-Keung, Karray, Fakhri, Hussain, Sadiq, Khosravi, Abbas, Acharya, U. Rajendra, Makarenkov, Vladimir and Nahavandi, Saeid (2023). UncertaintyFuseNet: Robust uncertainty-aware hierarchical feature fusion model with Ensemble Monte Carlo Dropout for COVID-19 detection. Information Fusion, 90, 364-381. doi: 10.1016/j.inffus.2022.09.023 |
