| Machine learning generalizability across healthcare settings: insights from multi-site COVID-19 screening J Yang, AAS Soltan, DA Clifton NPJ digital medicine 5 (1), 69, 2022 | 55 | 2022 |
| An adversarial training framework for mitigating algorithmic biases in clinical machine learning J Yang, AAS Soltan, DW Eyre, Y Yang, DA Clifton NPJ Digital Medicine 6 (1), 55, 2023 | 43* | 2023 |
| Real-world evaluation of rapid and laboratory-free COVID-19 triage for emergency care: external validation and pilot deployment of artificial intelligence driven screening AAS Soltan, J Yang, R Pattanshetty, A Novak, Y Yang, O Rohanian, ... The Lancet Digital Health 4 (4), e266-e278, 2022 | 40 | 2022 |
| Algorithmic fairness and bias mitigation for clinical machine learning with deep reinforcement learning J Yang, AAS Soltan, DW Eyre, DA Clifton Nature Machine Intelligence 5 (8), 884-894, 2023 | 31* | 2023 |
| Deep reinforcement learning for multi-class imbalanced training: applications in healthcare J Yang, R El-Bouri, O O’Donoghue, AS Lachapelle, AAS Soltan, DW Eyre, ... Machine Learning, 1-20, 2023 | 12* | 2023 |
| A scalable federated learning solution for secondary care using low-cost microcomputing: privacy-preserving development and evaluation of a COVID-19 screening test in UK hospitals AAS Soltan, A Thakur, J Yang, A Chauhan, LG D’Cruz, P Dickson, ... The Lancet Digital Health 6 (2), e93-e104, 2024 | 11* | 2024 |
| Machine learning-based risk stratification for gestational diabetes management J Yang, D Clifton, JE Hirst, FK Kavvoura, G Farah, L Mackillop, H Lu Sensors 22 (13), 4805, 2022 | 9 | 2022 |
| Digital health and machine learning technologies for blood glucose monitoring and management of gestational diabetes HY Lu, X Ding, JE Hirst, Y Yang, J Yang, L Mackillop, DA Clifton IEEE reviews in biomedical engineering 17, 98-117, 2023 | 8 | 2023 |
| A community-based approach to image analysis of cells, tissues and tumors JC Vizcarra, EA Burlingame, CB Hug, Y Goltsev, BS White, DR Tyson, ... Computerized Medical Imaging and Graphics 95, 102013, 2022 | 6 | 2022 |
| Standardising the assessment of caesarean birth using an oxford caesarean prediction score for mothers with gestational diabetes H Lu, J Hirst, J Yang, L Mackillop, D Clifton Healthcare Technology Letters 9 (1-2), 1-8, 2022 | 5 | 2022 |
| Privacy-aware early detection of COVID-19 through adversarial training O Rohanian, S Kouchaki, A Soltan, J Yang, M Rohanian, Y Yang, ... IEEE journal of biomedical and health informatics 27 (3), 1249-1258, 2022 | 4 | 2022 |
| Generalizability assessment of AI models across hospitals: a comparative study in low-middle income and high income countries J Yang, NT Dung, PN Thach, NT Phong, VD Phu, KD Phu, LM Yen, ... medRxiv, 2023.11. 05.23298109, 2023 | 3 | 2023 |
| Uncertainties in the Analysis of Heart Rate Variability: A Systematic Review L Lu, T Zhu, D Morelli, A Creagh, Z Liu, J Yang, F Liu, YT Zhang, ... IEEE Reviews in Biomedical Engineering, 2023 | 2 | 2023 |
| Deep Learning for Multi-Label Disease Classification of Retinal Images: Insights from Brazilian Data for AI Development in Lower-Middle Income Countries DSW Gould, J Yang, DA Clifton medRxiv, 2024.02. 12.24302676, 2024 | 1 | 2024 |
| Interpretable machine learning-based decision support for prediction of antibiotic resistance for complicated urinary tract infections J Yang, DW Eyre, L Lu, DA Clifton npj Antimicrobials and Resistance 1 (1), 14, 2023 | 1 | 2023 |
| Geometrically-aggregated training samples: Leveraging summary statistics to enable healthcare data democratization J Yang, A Thakur, AAS Soltan, DA Clifton medRxiv, 2023.10. 24.23297460, 2023 | 1 | 2023 |
| Mitigating machine learning bias between high income and low–middle income countries for enhanced model fairness and generalizability J Yang, L Clifton, NT Dung, NT Phong, LM Yen, DBX Thy, AAS Soltan, ... Scientific Reports 14 (1), 13318, 2024 | | 2024 |
| Reinforcement Learning for Imbalanced Vehicle Booming Noise Classification J Yang, DS Kunte, B Cornelis, DA Clifton 2023 2nd International Conference on Machine Learning, Control, and Robotics …, 2023 | | 2023 |
| Addressing Label Noise for Electronic Health Records: Insights from Computer Vision for Tabular Data J Yang, H Triendl, AAS Soltan, M Prakash, DA Clifton medRxiv, 2023.10. 17.23297136, 2023 | | 2023 |
| Using convolutional neural networks to predict NRG1-fusions in PDAC biopsy images J Yang University of British Columbia, 2020 | | 2020 |
