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Multimodal machine learning to predict surgical site infection with healthcare workload impact assessment
McLean KA, Sgro A, Brown LR, Buijs LF, Mountain KE, Shaw CA, Drake TM, Pius R, Knight SR, Fairfield CJ, Skipworth RJE, Tsaftaris SA, Wigmore SJ, Potter MA & Bouamrane M (2025) Multimodal machine learning to predict surgical site infection with healthcare workload impact assessment. npj Digital Medicine, 8, Art. No.: 121. https://doi.org/10.1038/s41746-024-01419-8
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Cross modality medical image synthesis for improving liver segmentation
Rafiq M, Ali H, Mujtaba G, Shah Z & Azmat S (2025) Cross modality medical image synthesis for improving liver segmentation. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 13 (1). https://doi.org/10.1080/21681163.2025.2476702
Interpretable decision trees to predict solution fitness
Catalano GAPI, Brownlee AEI, Cairns D & Ainslie R (2025) Interpretable decision trees to predict solution fitness. In: GECCO 2025, Malaga, Spain, 14.07.2025-18.07.2025. Association for Computing Machinery (ACM). https://doi.org/10.1145/1122445.1122456
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Information needs in vascular access decision-making: A qualitative study of patient and clinical stakeholder perspectives
Stevenson K, Meiklem R, Bouamrane M, Thomson P, Dunlop M, Martin L, Jones C & Kingsmore D (2025) Information needs in vascular access decision-making: A qualitative study of patient and clinical stakeholder perspectives. The Journal of Vascular Access, pp. 1-11. https://journals.sagepub.com/doi/10.1177/11297298251314792; https://doi.org/10.1177/11297298251314792
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An FPGA-based neuromorphic vision system accelerator
Ali T, Rainey J, Lau SY, Gheorghiu E, Maier P, Appiah K & Bhowmick D (2024) An FPGA-based neuromorphic vision system accelerator. In: Bouma H, Prabhu R, Yitzhaky Y & Kuijf HJ (eds.) volume 13206. SPIE "Artificial Intelligence for Security and Defence Applications II, Edinburgh, 16.09.2024-20.09.2024. SPIE. https://doi.org/10.1117/12.3034095
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Deep learning for surgical instrument recognition and segmentation in robotic-assisted surgeries: a systematic review
Ahmed FA, Yousef M, Ahmed MA, Ali HO, Mahboob A, Ali H, Shah Z, Aboumarzouk O, Al Ansari A & Balakrishnan S (2024) Deep learning for surgical instrument recognition and segmentation in robotic-assisted surgeries: a systematic review. Artificial Intelligence Review, 58 (1). https://doi.org/10.1007/s10462-024-10979-w
Combined Depth and Semantic Segmentation from Synthetic Data and a W-Net Architecture
Swingler K, Rumble T, Goutcher R, Hibbard P, Donoghue M & Harvey D (2024) Combined Depth and Semantic Segmentation from Synthetic Data and a W-Net Architecture. In: volume 1. 16th International Conference on Neural Computation Theory and Applications, Porto, Portugal, 20.11.2024-22.11.2024. SCITEPRESS - Science and Technology Publications, pp. 413-422. https://doi.org/10.5220/0012877500003837
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Semantically-Informed Graph Neural Networks for Irony Detection in Turkish
Bolucu N & Can Buglalilar B (2024) Semantically-Informed Graph Neural Networks for Irony Detection in Turkish. ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP).
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Advanced Mineral Deposit Mapping via Deep Learning and SVM Integration With Remote Sensing Imaging Data
Jan N, Minallah N, Sher M, Wasim M, Khan S, Al‐Rasheed A & Ali H (2024) Advanced Mineral Deposit Mapping via Deep Learning and SVM Integration With Remote Sensing Imaging Data. Engineering Reports, 7 (1). https://onlinelibrary.wiley.com/doi/full/10.1002/eng2.13031; https://doi.org/10.1002/eng2.13031
Conference Paper (published)
Uncertainty-Informed Model Selection Method for Nonlinear System Identification and Interpretable Machine Learning
Gu Y & Wei H (2024) Uncertainty-Informed Model Selection Method for Nonlinear System Identification and Interpretable Machine Learning. In: Proceedings of 2024 32nd Mediterranean Conference on Control and Automation (MED). 2024 32nd Mediterranean Conference on Control and Automation (MED), Chania - Crete, Greece, 11.06.2024-14.06.2024. IEEE, pp. 909-914. https://doi.org/10.1109/med61351.2024.10566184
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Single Stage Adaptive Multi-Attention Network for Image Restoration
Zafar A, Aftab D, Qureshi R, Fan X, Chen P, Wu J, Ali H, Nawaz S, Khan S & Shah M (2024) Single Stage Adaptive Multi-Attention Network for Image Restoration. IEEE Transactions on Image Processing, 33, pp. 2924-2935. https://doi.org/10.1109/tip.2024.3384838
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Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study
Abd-alrazaq A, Nashwan AJ, Shah Z, Abujaber A, Alhuwail D, Schneider J, AlSaad R, Ali H, Alomoush W, Ahmed A & Aziz S (2024) Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study. JMIR Formative Research, 8, Art. No.: e49411. https://doi.org/10.2196/49411
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High intensity interval training as a novel treatment for impaired awareness of hypoglycaemia in people with type 1 diabetes (HIT4HYPOS): a randomised parallel-group study
Farrell CM, McNeilly AD, Hapca S, Fournier PA, Jones TW, Facchinetti A, Cappon G, West DJ & McCrimmon RJ (2024) High intensity interval training as a novel treatment for impaired awareness of hypoglycaemia in people with type 1 diabetes (HIT4HYPOS): a randomised parallel-group study. Diabetologia, 67, pp. 392-402. https://doi.org/10.1007/s00125-023-06051-x
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Editorial: Recent advances in multimodal artificial intelligence for disease diagnosis, prognosis, and prevention
Ali H, Shah Z, Alam T, Wijayatunga P & Elyan E (2024) Editorial: Recent advances in multimodal artificial intelligence for disease diagnosis, prognosis, and prevention. Frontiers in Radiology, 3. https://doi.org/10.3389/fradi.2023.1349830
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Prototypical Contrastive Network for Imbalanced Aerial Image Segmentation
Nogueira K, Maezano Faita-Pinheiro M, Ramos AP, Gon?alves WN, Marcato Junior J & Santos JAD (2023) Prototypical Contrastive Network for Imbalanced Aerial Image Segmentation. In: WACV 2024, 04.01.2024-08.01.2024. Piscataway, NJ, USA: IEEE.
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Johnston P, Nogueira K & Swingler K (2023) GMM-IL: Image Classification Using Incrementally Learnt, Independent Probabilistic Models for Small Sample Sizes. IEEE Access, 11, pp. 25492-25501. https://doi.org/10.1109/access.2023.3255795
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Expected goals in football: Improving model performance and demonstrating value
Mead J, O’Hare A & McMenemy P (2023) Expected goals in football: Improving model performance and demonstrating value. Muazu Musa R (Editor) PLOS ONE, 18 (4), Art. No.: e0282295. https://doi.org/10.1371/journal.pone.0282295
Conference Paper (published)
MTLSegFormer: Multi-Task Learning With Transformers for Semantic Segmentation in Precision Agriculture
Goncalves DN, Junior JM, Zamboni P, Pistori H, Li J, Nogueira K & Goncalves W (2023) MTLSegFormer: Multi-Task Learning With Transformers for Semantic Segmentation in Precision Agriculture. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Vancouver, BC, Canada, 18.06.2023-22.06.2023. Piscataway, NJ, USA: IEEE, pp. 6290-6298. https://doi.org/10.1109/CVPRW59228.2023.00669