| Long-term enhancement of brain function and cognition using cognitive training and brain stimulation A Snowball, I Tachtsidis, T Popescu, J Thompson, M Delazer, L Zamarian, ... Current Biology 23 (11), 987-992, 2013 | 380 | 2013 |
| Clocs: Contrastive learning of cardiac signals across space, time, and patients D Kiyasseh, T Zhu, DA Clifton International Conference on Machine Learning, 5606-5615, 2021 | 215 | 2021 |
| Noninvasive fetal ECG: the PhysioNet/computing in cardiology challenge 2013 I Silva, J Behar, R Sameni, T Zhu, J Oster, GD Clifford, GB Moody Computing in cardiology 2013, 149-152, 2013 | 213 | 2013 |
| Machine learning for clinical outcome prediction F Shamout, T Zhu, DA Clifton IEEE reviews in Biomedical Engineering 14, 116-126, 2020 | 177 | 2020 |
| Machine learning for classifying tuberculosis drug-resistance from DNA sequencing data Y Yang, KE Niehaus, TM Walker, Z Iqbal, AS Walker, DJ Wilson, TEA Peto, ... Bioinformatics 34 (10), 1666-1671, 2018 | 145 | 2018 |
| Rapid triage for COVID-19 using routine clinical data for patients attending hospital: development and prospective validation of an artificial intelligence screening test AAS Soltan, S Kouchaki, T Zhu, D Kiyasseh, T Taylor, ZB Hussain, T Peto, ... The Lancet Digital Health 3 (2), e78-e87, 2021 | 133 | 2021 |
| Brain mitochondrial oxidative metabolism during and after cerebral hypoxia–ischemia studied by simultaneous phosphorus magnetic-resonance and broadband near-infrared spectroscopy A Bainbridge, I Tachtsidis, SD Faulkner, D Price, T Zhu, E Baer, KD Broad, ... Neuroimage 102, 173-183, 2014 | 108 | 2014 |
| Deep interpretable early warning system for the detection of clinical deterioration FE Shamout, T Zhu, P Sharma, PJ Watkinson, DA Clifton IEEE journal of biomedical and health informatics 24 (2), 437-446, 2019 | 93 | 2019 |
| Generating synthetic mixed-type longitudinal electronic health records for artificial intelligent applications J Li, BJ Cairns, J Li, T Zhu NPJ digital medicine 6 (1), 98, 2023 | 86 | 2023 |
| External validation of AI models in health should be replaced with recurring local validation A Youssef, M Pencina, A Thakur, T Zhu, D Clifton, NH Shah nature medicine 29 (11), 2686-2687, 2023 | 80 | 2023 |
| PlethAugment: GAN-based PPG augmentation for medical diagnosis in low-resource settings D Kiyasseh, GA Tadesse, L Thwaites, T Zhu, D Clifton IEEE journal of biomedical and health informatics 24 (11), 3226-3235, 2020 | 80 | 2020 |
| Assessing computerized eye tracking technology for gaining insight into expert interpretation of the 12-lead electrocardiogram: an objective quantitative approach RR Bond, T Zhu, DD Finlay, B Drew, PD Kligfield, D Guldenring, C Breen, ... Journal of electrocardiology 47 (6), 895-906, 2014 | 79 | 2014 |
| A medical multimodal large language model for future pandemics F Liu, T Zhu, X Wu, B Yang, C You, C Wang, L Lu, Z Liu, Y Zheng, X Sun, ... NPJ Digital Medicine 6 (1), 226, 2023 | 76 | 2023 |
| A survey of generative adversarial networks for synthesizing structured electronic health records GO Ghosheh, J Li, T Zhu ACM Computing Surveys 56 (6), 1-34, 2024 | 73* | 2024 |
| The 2023 wearable photoplethysmography roadmap PH Charlton, J Allen, R Bailón, S Baker, JA Behar, F Chen, GD Clifford, ... Physiological measurement 44 (11), 111001, 2023 | 70 | 2023 |
| Optimal wavelength combinations for near-infrared spectroscopic monitoring of changes in brain tissue hemoglobin and cytochrome c oxidase concentrations D Arifler, T Zhu, S Madaan, I Tachtsidis Biomedical Optics Express 6 (3), 933-947, 2015 | 64 | 2015 |
| Stroke risk prediction using machine learning: a prospective cohort study of 0.5 million Chinese adults M Chun, R Clarke, BJ Cairns, D Clifton, D Bennett, Y Chen, Y Guo, P Pei, ... Journal of the American Medical Informatics Association 28 (8), 1719-1727, 2021 | 63 | 2021 |
| DeepAMR for predicting co-occurrent resistance of Mycobacterium tuberculosis Y Yang, TM Walker, AS Walker, DJ Wilson, TEA Peto, DW Crook, ... Bioinformatics 35 (18), 3240-3249, 2019 | 57 | 2019 |
| Artificial intelligence for mechanical ventilation: systematic review of design, reporting standards, and bias J Gallifant, J Zhang, MPA Lopez, T Zhu, L Camporota, LA Celi, F Formenti British Journal of Anaesthesia 128 (2), 343-351, 2022 | 51 | 2022 |
| A clinical deep learning framework for continually learning from cardiac signals across diseases, time, modalities, and institutions D Kiyasseh, T Zhu, D Clifton Nature Communications 12 (1), 4221, 2021 | 50 | 2021 |
David A. CliftonChair of Clinical Machine Learning, University of OxfordVerified email at eng.ox.ac.uk
