| A machine learning cardiac magnetic resonance approach to extract disease features and automate pulmonary arterial hypertension diagnosis AJ Swift, H Lu, J Uthoff, P Garg, M Cogliano, J Taylor, P Metherall, S Zhou, ... European Heart Journal-Cardiovascular Imaging 22 (2), 236-245, 2021 | 62 | 2021 |
| Improving multi-site autism classification via site-dependence minimization and second-order functional connectivity M Kunda, S Zhou, G Gong, H Lu IEEE Transactions on Medical Imaging 42 (1), 55-65, 2022 | 37* | 2022 |
| Neuropsychiatric disease classification using functional connectomics-results of the connectomics in neuroimaging transfer learning challenge MD Schirmer, A Venkataraman, I Rekik, M Kim, SH Mostofsky, MB Nebel, ... Medical image analysis 70, 101972, 2021 | 25 | 2021 |
| Machine learning cardiac-MRI features predict mortality in newly diagnosed pulmonary arterial hypertension S Alabed, J Uthoff, S Zhou, P Garg, K Dwivedi, F Alandejani, R Gosling, ... European Heart Journal-Digital Health 3 (2), 265-275, 2022 | 17 | 2022 |
| Side information dependence as a regularizer for analyzing human brain conditions across cognitive experiments S Zhou, W Li, C Cox, H Lu Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 6957-6964, 2020 | 14* | 2020 |
| Improving whole-brain neural decoding of fmri with domain adaptation S Zhou, CR Cox, H Lu International workshop on machine learning in medical imaging, 265-273, 2019 | 14 | 2019 |
| PyKale: Knowledge-aware machine learning from multiple sources in Python H Lu, X Liu, S Zhou, R Turner, P Bai, RE Koot, M Chasmai, L Schobs, ... Proceedings of the 31st ACM International Conference on Information …, 2022 | 6 | 2022 |
| Sturm: Sparse tubal-regularized multilinear regression for fmri W Li, J Lou, S Zhou, H Lu International Workshop on Machine Learning in Medical Imaging, 256-264, 2019 | 5 | 2019 |
| Confidence-quantifying landmark localisation for cardiac MRI L Schobs, S Zhou, M Cogliano, AJ Swift, H Lu 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 985-988, 2021 | 4 | 2021 |
| Tensor-based multimodal learning for prediction of pulmonary arterial wedge pressure from cardiac MRI PC Tripathi, MNI Suvon, L Schobs, S Zhou, S Alabed, AJ Swift, H Lu International Conference on Medical Image Computing and Computer-Assisted …, 2023 | 3 | 2023 |
| First-person video domain adaptation with multi-scene cross-site datasets and attention-based methods X Liu, S Zhou, T Lei, P Jiang, Z Chen, H Lu IEEE Transactions on Circuits and Systems for Video Technology 33 (12), 7774 …, 2023 | 3 | 2023 |
| MeDSLIP: Medical Dual-Stream Language-Image Pre-training for Fine-grained Alignment W Fan, MNI Suvon, S Zhou, X Liu, S Alabed, V Osmani, A Swift, C Chen, ... arXiv preprint arXiv:2403.10635, 2024 | 2 | 2024 |
| Direct ICA on data tensor via random matrix modeling L Song, S Zhou, H Lu Signal Processing 196, 108508, 2022 | 2 | 2022 |
| Interpretable Domain-Aware Learning for Neuroimage Classification S Zhou University of Sheffield, 2022 | 2 | 2022 |
| Group-specific discriminant analysis reveals statistically validated sex differences in lateralization of brain functional network S Zhou, J Luo, Y Jiang, H Wang, H Lu, G Gong arXiv preprint arXiv:2404.05781, 2024 | | 2024 |
| Interpretable Multimodal Learning for Cardiovascular Hemodynamics Assessment PC Tripathi, S Tabakhi, MNI Suvon, L Schöb, S Alabed, AJ Swift, S Zhou, ... arXiv preprint arXiv:2404.04718, 2024 | | 2024 |
| Multimodal Variational Autoencoder for Low-cost Cardiac Hemodynamics Instability Detection MNI Suvon, PC Tripathi, W Fan, S Zhou, X Liu, S Alabed, V Osmani, ... arXiv preprint arXiv:2403.13658, 2024 | | 2024 |
| Channel-Temporal Attention for First-Person Video Domain Adaptation X Liu, S Zhou, T Lei, H Lu arXiv preprint arXiv:2108.07846, 2021 | | 2021 |
| Team PyKale (xy9) Submission to the EPIC-Kitchens 2021 Unsupervised Domain Adaptation Challenge for Action Recognition X Liu, R Koot, S Zhou, T Lei, H Lu arXiv preprint arXiv:2106.12023, 2021 | | 2021 |
| A Biased Sampling Network to Localise Landmarks for Automated Disease Diagnosis L Schobs, S Zhou, M Cogliano, AJ Swift, H Lu | | |
Haiping LuProfessor of Machine Learning, University of Sheffield在 sheffield.ac.uk 的电子邮件经过验证
