Publications

Digital Health Publications
Independent external validation of the QRISK3 cardiovascular disease risk prediction model using UK Biobank.
Parsons RE, Liu X, Collister JA, Clifton DA, Cairns BJ et al. (2023), Heart (British Cardiac Society), heartjnl-2022-321231
BibTeX
@article{independentexte-2023/7,
title={Independent external validation of the QRISK3 cardiovascular disease risk prediction model using UK Biobank.},
author={Parsons RE, Liu X, Collister JA, Clifton DA, Cairns BJ et al.},
journal={Heart (British Cardiac Society)},
pages={heartjnl-2022-321231},
year = "2023"
}
Clinical benefit of AI-assisted lung ultrasound in a resource-limited intensive care unit.
Nhat PTH, Van Hao N, Tho PV, Kerdegari H, Pisani L et al. (2023), Critical care (London, England), 27(1), 257
BibTeX
@article{clinicalbenefit-2023/7,
title={Clinical benefit of AI-assisted lung ultrasound in a resource-limited intensive care unit.},
author={Nhat PTH, Van Hao N, Tho PV, Kerdegari H, Pisani L et al.},
journal={Critical care (London, England)},
volume={27},
number={ARTN 257},
pages={257},
publisher={Springer Nature},
year = "2023"
}
Improving Diagnostics with Deep Forest Applied to Electronic Health Records
Khodadad A, Ghanbari Bousejin N, Molaei S, Kumar Chauhan V, Zhu T et al. (2023), Sensors
The 2023 wearable photoplethysmography roadmap.
Charlton PH, Allen J, Bailon R, Baker S, Behar JA et al. (2023), Physiological measurement
Improving Diagnostics with Deep Forest Applied to Electronic Health Records
Khodadad A, Ghanbari Bousejin N, Molaei S, Kumar Chauhan V, Zhu T et al. (2023), Sensors
A Multimodal Large Language Modelling Deep Learning Framework for the Future Pandemic
Liu F, Zhu T, Wu X, Yang B, You C et al. (2023)
DyVGRNN: DYnamic mixture variational graph recurrent neural networks
Niknam G, Molaei S, Zare H, Pan S, Jalili M et al. (2023), Neural Networks, 165, 596-610
DyVGRNN: DYnamic mixture Variational Graph Recurrent Neural Networks
Niknam G, MOLAEI S, Zare H, Pan S, Jalili M et al. (2023), Neural Networks
DyVGRNN: DYnamic mixture variational graph recurrent neural networks
Niknam G, Molaei S, Zare H, Pan S, Jalili M et al. (2023), Neural Networks, 165, 596-610
Synthesizing Electronic Health Records for Predictive Models in Low-Middle-Income Countries (LMICs).
Ghosheh GO, Thwaites CL & Zhu T (2023), Biomedicines, 11(6), 1749
DyVGRNN: DYnamic mixture Variational Graph Recurrent Neural Networks
Niknam G, MOLAEI S, Zare H, Pan S, Jalili M et al. (2023), Neural Networks
Uncertainties in the analysis of heart rate variability: a systematic review
Lu L, Zhu T, Morelli D, Creagh A, Liu Z et al. (2023), IEEE Reviews in Biomedical Engineering
Dynamic inter-treatment information sharing for heterogeneous treatment effects estimation
Chauhan VK, Zhou J, Molaei S, Ghosheh G & Clifton DA (2023)
Scalable federated learning for emergency care using low cost microcomputing: Real-world, privacy preserving development and evaluation of a COVID-19 screening test in UK hospitals
Soltan AAS, Thakur A, Yang J, Chauhan A, D’Cruz LG et al. (2023)
BibTeX
@misc{scalablefederat-2023/5,
title={Scalable federated learning for emergency care using low cost microcomputing: Real-world, privacy preserving development and evaluation of a COVID-19 screening test in UK hospitals},
author={Soltan AAS, Thakur A, Yang J, Chauhan A, D’Cruz LG et al.},
year = "2023"
}
Generating synthetic mixed-type longitudinal electronic health records for artificial intelligent applications.
Li J, Cairns BJ, Li J & Zhu T (2023), NPJ digital medicine, 6(1), 98
Uncertainties in the analysis of heart rate variability: a systematic review
Lu L, Zhu T, Morelli D, Creagh A, Liu Z et al. (2023), IEEE Reviews in Biomedical Engineering
Clinical decision support systems used in transplantation: are they tools for success or an unnecessary gadget? A systematic review
Wingfield L, Salaun A, Khan A, Webb H, Zhu T et al. (2023), Transplantation
BibTeX
@article{clinicaldecisio-2023/5,
title={Clinical decision support systems used in transplantation: are they tools for success or an unnecessary gadget? A systematic review},
author={Wingfield L, Salaun A, Khan A, Webb H, Zhu T et al.},
journal={Transplantation},
publisher={Lippincott, Williams & Wilkins},
year = "2023"
}
IMAE for noise-robust learning: mean absolute error does not treat examples equally and gradient magnitude’s variance matters
Wang X, Hua Y, Kodirov E, Clifton D & Robertson NM (2023)
BibTeX
@inproceedings{imaefornoiserob-2023/4,
title={IMAE for noise-robust learning: mean absolute error does not treat examples equally and gradient magnitude’s variance matters},
author={Wang X, Hua Y, Kodirov E, Clifton D & Robertson NM},
booktitle={ICLR 2023 Workshop on Trustworthy and Reliable Large-Scale Machine Learning Models},
year = "2023"
}
An adversarial training framework for mitigating algorithmic biases in clinical machine learning.
Yang J, Soltan AAS, Eyre DW, Yang Y & Clifton DA (2023), NPJ Digit Med, 6(1), 55
Heterogeneity in the diagnosis and prognosis of ischemic stroke subtypes: 9-year follow-up of 22,000 cases in Chinese adults.
Chun M, Qin H, Turnbull I, Sansome S, Gilbert S et al. (2023), International journal of stroke : official journal of the International Stroke Society, 17474930231162265
BibTeX
@article{heterogeneityin-2023/3,
title={Heterogeneity in the diagnosis and prognosis of ischemic stroke subtypes: 9-year follow-up of 22,000 cases in Chinese adults.},
author={Chun M, Qin H, Turnbull I, Sansome S, Gilbert S et al.},
journal={International journal of stroke : official journal of the International Stroke Society},
pages={17474930231162265},
publisher={SAGE Publications},
year = "2023"
}
Heterogeneity in diagnosis and prognosis of ischaemic stroke subtypes: 9-year follow-up of 22000 cases in Chinese adults.
Chun M, Qin H, Turnbull I, Sansome S, Gilbert S et al. (2023), Int J Stroke, 17474930231162265
BibTeX
@article{heterogeneityin-2023/2,
title={Heterogeneity in diagnosis and prognosis of ischaemic stroke subtypes: 9-year follow-up of 22000 cases in Chinese adults.},
author={Chun M, Qin H, Turnbull I, Sansome S, Gilbert S et al.},
journal={Int J Stroke},
pages={17474930231162265},
year = "2023"
}
On the Effectiveness of Compact Biomedical Transformers.
Rohanian O, Nouriborji M, Kouchaki S & Clifton DA (2023), Bioinformatics
SeroTracker-RoB: a decision rule-based algorithm for reproducible risk of bias assessment of seroprevalence studies.
Bobrovitz N, Noël K, Li Z, Cao C, Deveaux G et al. (2023), Research synthesis methods
Patient Clustering for Vital Organ Failure Using ICD Code with Graph Attention
Liu Z, Hu Y, Wu X, Mertes G, Yang Y et al. (2023), IEEE Transactions on Biomedical Engineering
Self-Aware SGD: Reliable Incremental Adaptation Framework For Clinical AI Models
Thakur A, Armstrong J, Youssef A, Eyre D & Clifton DA (2023), IEEE Journal of Biomedical and Health Informatics, 1-11
BibTeX
@article{selfawaresgdrel-2023/1,
title={Self-Aware SGD: Reliable Incremental Adaptation Framework For Clinical AI Models},
author={Thakur A, Armstrong J, Youssef A, Eyre D & Clifton DA},
journal={IEEE Journal of Biomedical and Health Informatics},
pages={1-11},
publisher={Institute of Electrical and Electronics Engineers (IEEE)},
year = "2023"
}
Multimodal Learning With Transformers: A Survey
Xu P, Zhu X & Clifton DA (2023), IEEE Transactions on Pattern Analysis and Machine Intelligence
MiniALBERT: Model Distillation via Parameter-Efficient Recursive Transformers
Nouriborji M, Rohanian O, Kouchaki S & Clifton DA (2023), EACL 2023 - 17th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference, 1153-1165
BibTeX
@inproceedings{minialbertmodel-2023/1,
title={MiniALBERT: Model Distillation via Parameter-Efficient Recursive Transformers},
author={Nouriborji M, Rohanian O, Kouchaki S & Clifton DA},
pages={1153-1165},
year = "2023"
}
Bedaquiline and clofazimine resistance in Mycobacterium tuberculosis: an in-vitro and in-silico data analysis
Sonnenkalb L, Carter J, Spitaleri A, Iqbal Z, Hunt M et al. (2023), The Lancet Microbe
Adversarial De-confounding in Individualised Treatment Effects Estimation
Chauhan VK, Molaei S, Tania MH, Thakur A, Zhu T et al. (2023), Proceedings of Machine Learning Research, 206, 837-849
BibTeX
@inproceedings{adversarialdeco-2023/1,
title={Adversarial De-confounding in Individualised Treatment Effects Estimation},
author={Chauhan VK, Molaei S, Tania MH, Thakur A, Zhu T et al.},
pages={837-849},
year = "2023"
}
Algorithmic fairness and bias mitigation for clinical machine learning with deep reinforcement learning
Yang J, Soltan AAS, Eyre DW & Clifton DA (2023), Nature Machine Intelligence
Adversarial De-confounding in Individualised Treatment Effects Estimation
Chauhan VK, Molaei S, Tania MH, Thakur A, Zhu T et al. (2023), Proceedings of Machine Learning Research, 206, 837-849
BibTeX
@inproceedings{adversarialdeco-2023/1,
title={Adversarial De-confounding in Individualised Treatment Effects Estimation},
author={Chauhan VK, Molaei S, Tania MH, Thakur A, Zhu T et al.},
pages={837-849},
year = "2023"
}
A Framework For Motor Function Characterization in Autism Spectrum Disorder
Paulo JR, Sousa T, Perdiz J, Leal N, Menezes P et al. (2023), 2023 IEEE 7th Portuguese Meeting on Bioengineering, ENBENG 2023, 104-107
Features from the photoplethysmogram and the electrocardiogram for estimating changes in blood pressure.
Finnegan E, Davidson S, Harford M, Watkinson P, Tarassenko L et al. (2023), Scientific reports, 13(1), 986
BibTeX
@article{featuresfromthe-2023/1,
title={Features from the photoplethysmogram and the electrocardiogram for estimating changes in blood pressure.},
author={Finnegan E, Davidson S, Harford M, Watkinson P, Tarassenko L et al.},
journal={Scientific reports},
volume={13},
pages={986},
year = "2023"
}
Development and Validation of a Machine Learning Wrist-worn Step Detection Algorithm with Deployment in the UK Biobank
Small S, Chan S, Walmsley R, Fritsch LV, Acquah A et al. (2023)
Evaluation of awake prone positioning effectiveness in moderate to severe COVID-19
Truong NT, Phong NT, Nguyen NT, Khanh LTT, Tran LHB et al. (2023)
Scalable federated learning for emergency care using low cost microcomputing: Real-world, privacy preserving development and evaluation of a COVID-19 screening test in UK hospitals
Soltan A, Thakur A, Yang J, Chauhan A, D’Cruz L et al. (2023)
BibTeX
@misc{scalablefederat-2023/,
title={Scalable federated learning for emergency care using low cost microcomputing: Real-world, privacy preserving development and evaluation of a COVID-19 screening test in UK hospitals},
author={Soltan A, Thakur A, Yang J, Chauhan A, D’Cruz L et al.},
year = "2023"
}
Data Encoding For Healthcare Data Democratisation and Information Leakage Prevention
Zhu T, Armstrong J, Abrol V, Wang Y, Clifton D et al. (2023)
A Large Language Modelling Deep Learning Framework for the Next Pandemic
Zhu T, Wu X, Yang B, You C, Wang C et al. (2023)
Data Encoding For Healthcare Data Democratisation and Information Leakage Prevention
Zhu T, Armstrong J, Abrol V, Wang Y, Clifton D et al. (2023)
A Large Language Modelling Deep Learning Framework for the Next Pandemic
Zhu T, Wu X, Yang B, You C, Wang C et al. (2023)
Graph representation learning based on deep generative gaussian mixture models
Niknam G, Molaei S, Zare H, Clifton D & Pan S (2022), Neurocomputing, 523, 157-169
Wearable vital signs monitoring for patients with asthma: a review
Talyor L, Ding X, Clifton D & Lu HY (2022), IEEE Sensors Journal
Serology Assays Used in SARS-CoV-2 Seroprevalence Surveys Worldwide: A Systematic Review and Meta-Analysis of Assay Features, Testing Algorithms, and Performance.
Ma X, Li Z, Whelan MG, Kim D, Cao C et al. (2022), Vaccines, 10(12), 2000
BibTeX
@article{serologyassaysu-2022/11,
title={Serology Assays Used in SARS-CoV-2 Seroprevalence Surveys Worldwide: A Systematic Review and Meta-Analysis of Assay Features, Testing Algorithms, and Performance. },
author={Ma X, Li Z, Whelan MG, Kim D, Cao C et al.},
journal={Vaccines},
volume={10},
pages={2000},
year = "2022"
}
Global SARS-CoV-2 seroprevalence from January 2020 to April 2022: A systematic review and meta-analysis of standardized population-based studies.
Bergeri I, Whelan MG, Ware H, Subissi L, Nardone A et al. (2022), PLoS medicine, 19(11), e1004107
BibTeX
@article{globalsarscovse-2022/11,
title={Global SARS-CoV-2 seroprevalence from January 2020 to April 2022: A systematic review and meta-analysis of standardized population-based studies.},
author={Bergeri I, Whelan MG, Ware H, Subissi L, Nardone A et al.},
journal={PLoS medicine},
volume={19},
pages={e1004107},
year = "2022"
}
Contactless skin perfusion monitoring with video cameras: tracking pharmacological vasoconstriction and vasodilation using photoplethysmographic changes
Harford M, Villarroel M, Jorge J, Redfern O, Finnegan E et al. (2022), Physiological Measurement, 43(11)
BibTeX
@article{contactlessskin-2022/11,
title={Contactless skin perfusion monitoring with video cameras: tracking pharmacological vasoconstriction and vasodilation using photoplethysmographic changes},
author={Harford M, Villarroel M, Jorge J, Redfern O, Finnegan E et al.},
journal={Physiological Measurement},
volume={43},
number={115001},
publisher={IOP Publishing},
year = "2022"
}
Improving classification of tetanus severity for patients in low-middle income countries wearing ECG sensors by using a CNN-transformer network
Lu P, Wang C, Hagenah J, Ghiasi S, Zhu T et al. (2022), IEEE Transactions on Biomedical Engineering
BibTeX
@article{improvingclassi-2022/10,
title={Improving classification of tetanus severity for patients in low-middle income countries wearing ECG sensors by using a CNN-transformer network},
author={Lu P, Wang C, Hagenah J, Ghiasi S, Zhu T et al.},
journal={IEEE Transactions on Biomedical Engineering},
publisher={IEEE},
year = "2022"
}
Publisher Correction: Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI.
Vasey B, Nagendran M, Campbell B, Clifton DA, Collins GS et al. (2022), Nature medicine, 28(10), 2218
BibTeX
@article{publishercorrec-2022/10,
title={Publisher Correction: Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI.},
author={Vasey B, Nagendran M, Campbell B, Clifton DA, Collins GS et al.},
journal={Nature medicine},
volume={28},
pages={2218},
year = "2022"
}
Adversarial de-confounding in individualised treatment effects estimation
Kumar V, Molaei S, Hoque Tania M, Thakur A, Zhu T et al. (2022), arXiv
Timeliness of reporting of SARS-CoV-2 seroprevalence results and their utility for infectious disease surveillance.
Donnici C, Ilincic N, Cao C, Zhang C, Deveaux G et al. (2022), Epidemics, 41, 100645