Showing 50 publications by David Clifton
A multimodal automated deep learning-based model for predicting biochemical recurrence of prostate cancer following prostatectomy from baseline MRI, Presurgical clinical covariates
Simon BD, Harmon SA, Merriman KM, Tetreault J, Esengur OT et al. (2025), Clinical Imaging, 126, 110579
BibTeX
@article{amultimodalauto-2025/10,
title={A multimodal automated deep learning-based model for predicting biochemical recurrence of prostate cancer following prostatectomy from baseline MRI, Presurgical clinical covariates},
author={Simon BD, Harmon SA, Merriman KM, Tetreault J, Esengur OT et al.},
journal={Clinical Imaging},
volume={126},
pages={110579},
publisher={Elsevier},
year = "2025"
}
Development and external validation of a clinical prediction model for new-onset atrial fibrillation in intensive care: a multicentre, retrospective cohort study.
Bedford JP, Redfern O, Gerry S, Hatch R, Keating L et al. (2025), The Lancet. Digital health, 100896
BibTeX
@article{developmentande-2025/9,
title={Development and external validation of a clinical prediction model for new-onset atrial fibrillation in intensive care: a multicentre, retrospective cohort study.},
author={Bedford JP, Redfern O, Gerry S, Hatch R, Keating L et al.},
journal={The Lancet. Digital health},
number={100896},
pages={100896},
publisher={Elsevier BV},
year = "2025"
}
Learning Across the Divide: Personalised Federated Learning for Robust Clinical Modelling under Data-View Heterogeneity
Molaei S, Thakur A, Clifton L, Soltan A, Schwab P et al. (2025), IEEE Journal of Biomedical and Health Informatics, PP(99), 1-10
BibTeX
@article{learningacrosst-2025/9,
title={Learning Across the Divide: Personalised Federated Learning for Robust Clinical Modelling under Data-View Heterogeneity},
author={Molaei S, Thakur A, Clifton L, Soltan A, Schwab P et al.},
journal={IEEE Journal of Biomedical and Health Informatics},
volume={PP},
pages={1-10},
publisher={Institute of Electrical and Electronics Engineers (IEEE)},
year = "2025"
}
A collaborative large language model for drug analysis
Zhou H, Liu F, Wu J, Zhang W, Huang G et al. (2025), Nature Biomedical Engineering, 1-12
Dynamic Beat-to-Beat Measurements of Blood Pressure Using Multimodal Physiological Signals and a Hybrid CNN-LSTM Model
Xiang T, Jin Y, Liu Z, Clifton L, Clifton DA et al. (2025), IEEE Journal of Biomedical and Health Informatics, 29(8), 5438-5451
BibTeX
@article{dynamicbeattobe-2025/8,
title={Dynamic Beat-to-Beat Measurements of Blood Pressure Using Multimodal Physiological Signals and a Hybrid CNN-LSTM Model},
author={Xiang T, Jin Y, Liu Z, Clifton L, Clifton DA et al.},
journal={IEEE Journal of Biomedical and Health Informatics},
volume={29},
pages={5438-5451},
publisher={Institute of Electrical and Electronics Engineers (IEEE)},
year = "2025"
}
Beyond correlations: the necessity and the challenges of causal AI
Chauhan VK, Dhami DS, Gao B, Wang X, Clifton L et al. (2025)
Bridging the generalisation gap: synthetic data generation for multi-site clinical model validation
Segal B, Fieggen J, Clifton D & Clifton L (2025)
BibTeX
@inproceedings{bridgingthegene-2025/7,
title={Bridging the generalisation gap: synthetic data generation for multi-site clinical model validation},
author={Segal B, Fieggen J, Clifton D & Clifton L},
booktitle={47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society},
year = "2025"
}
Guest Editorial: Introduction to the Special Section on Large-Scale Multimodal Learning: Universality, Robustness, Efficiency, and Beyond
Xu P, Bai S, Zhou B, Clifton D, Vedaldi A et al. (2025), IEEE Transactions on Pattern Analysis and Machine Intelligence, 47(7), 5127-5129
BibTeX
@article{guesteditoriali-2025/7,
title={Guest Editorial: Introduction to the Special Section on Large-Scale Multimodal Learning: Universality, Robustness, Efficiency, and Beyond},
author={Xu P, Bai S, Zhou B, Clifton D, Vedaldi A et al.},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume={47},
pages={5127-5129},
publisher={Institute of Electrical and Electronics Engineers (IEEE)},
year = "2025"
}
Efficient Task Grouping Through Sample-wise Optimisation Landscape Analysis
Thakur A, Huang Y, Molaei S, Wang Y & Clifton DA (2025), IEEE Transactions on Pattern Analysis and Machine Intelligence, PP(99), 1-14
BibTeX
@article{efficienttaskgr-2025/7,
title={Efficient Task Grouping Through Sample-wise Optimisation Landscape Analysis},
author={Thakur A, Huang Y, Molaei S, Wang Y & Clifton DA},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume={PP},
pages={1-14},
publisher={Institute of Electrical and Electronics Engineers (IEEE)},
year = "2025"
}
Epidemiology of Thrombotic Thrombocytopenia Syndrome 2011 to 2022: English Sentinel Network Cohort Studies
Ordóñez-Mena JM, Kar D, Fan X, Ferreira F, Anand SN et al. (2025), Drug Safety, 1-15
BibTeX
@article{epidemiologyoft-2025/7,
title={Epidemiology of Thrombotic Thrombocytopenia Syndrome 2011 to 2022: English Sentinel Network Cohort Studies},
author={Ordóñez-Mena JM, Kar D, Fan X, Ferreira F, Anand SN et al.},
journal={Drug Safety},
pages={1-15},
publisher={Springer Nature},
year = "2025"
}
Continual learning across population cohorts with distribution shift: insights from multi-cohort metabolic syndrome identification.
Liu C, Liu Z, Liu J, Cai C, Clifton DA et al. (2025), Journal of the American Medical Informatics Association : JAMIA, ocaf070
BibTeX
@article{continuallearni-2025/6,
title={Continual learning across population cohorts with distribution shift: insights from multi-cohort metabolic syndrome identification.},
author={Liu C, Liu Z, Liu J, Cai C, Clifton DA et al.},
journal={Journal of the American Medical Informatics Association : JAMIA},
pages={ocaf070},
publisher={Oxford University Press (OUP)},
year = "2025"
}
Sensing Cardiac Health Across Scenarios and Devices: A Multi-Modal Foundation Model Pretrained on Heterogeneous Data from 1.7 Million Individuals
Gu X, Tang W, Han J, Sangha V, Liu F et al. (2025)
BibTeX
@misc{sensingcardiach-2025/6,
title={Sensing Cardiac Health Across Scenarios and Devices: A Multi-Modal Foundation Model Pretrained on Heterogeneous Data from 1.7 Million Individuals},
author={Gu X, Tang W, Han J, Sangha V, Liu F et al.},
year = "2025"
}
F3OCUS - Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics
Saha P, Wagner F, Mishra D, Peng C, Thakur A et al. (2025), 00, 20006-20017
BibTeX
@inproceedings{focusfederatedf-2025/6,
title={F3OCUS - Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics},
author={Saha P, Wagner F, Mishra D, Peng C, Thakur A et al.},
booktitle={2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
pages={20006-20017},
year = "2025"
}
Awake Prone Positioning in Adults With COVID-19
Luo J, Pavlov I, Tavernier E, Perez Y, Kharat A et al. (2025), JAMA Internal Medicine, 185(5), 572-581
Transformers for rapid detection of airway stenosis and stridor
Anibal J, Doctor R, Boyer M, Newberry K, De Santiago I et al. (2025), Scientific Reports, 15(1)
Dysregulated immune proteins in plasma in the UK Biobank predict Multiple Myeloma 12 years before clinical diagnosis
Fieggen J, Thakur A, Butler CC, Ramasamy K, Thakurta A et al. (2025), Blood Advances
BibTeX
@article{dysregulatedimm-2025/5,
title={Dysregulated immune proteins in plasma in the UK Biobank predict Multiple Myeloma 12 years before clinical diagnosis},
author={Fieggen J, Thakur A, Butler CC, Ramasamy K, Thakurta A et al.},
journal={Blood Advances},
publisher={American Society of Hematology},
year = "2025"
}
Benchmarking transformer-based models for medical record deidentification: A single centre, multi-specialty evaluation
Kuo R, Soltan AAS, O'Hanlon C, Hasanic A, Clifton DA et al. (2025)
MISE: meta-knowledge inheritance for social media-based stressor estimation
Wang X, Feng L, Zhang H, Cao L, Zeng K et al. (2025), WWW '25: Proceedings of the ACM on Web Conference 2025, 1866-1876
Application of large language models in medicine
Liu F, Zhou H, Gu B, Zou X, Huang J et al. (2025), Nature Reviews Bioengineering
A scoping review of large language models for generative tasks in mental health care
Hua Y, Na H, Li Z, Liu F, Fang X et al. (2025), npj Digital Medicine, 8(1)
Microtitre Plate Image Augmentation with Generative Adversarial Networks
Li R, Chai T, Kouchaki S, Clifton D & Yang Y (2025), ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 00, 1-5
BibTeX
@inproceedings{microtitreplate-2025/4,
title={Microtitre Plate Image Augmentation with Generative Adversarial Networks},
author={Li R, Chai T, Kouchaki S, Clifton D & Yang Y},
booktitle={ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
pages={1-5},
year = "2025"
}
Bridging the Generalisation Gap: Synthetic Data Generation for Multi-Site Clinical Model Validation
Segal B, Fieggen J, Clifton D & Clifton L (2025)
RiskAgent: Autonomous Medical AI Copilot for Generalist Risk Prediction
Liu F, Wu J, Zhou H, Gu X, Molaei S et al. (2025)
A multimodal multidomain multilingual medical foundation model for zero shot clinical diagnosis
Liu F, Li Z, Yin Q, Huang J, Luo J et al. (2025), npj Digital Medicine, 8(1)
Status of Digital Health Technology Adoption in 5 Vietnamese Hospitals: Cross-Sectional Assessment.
Tran DM, Thanh Dung N, Minh Duc C, Ngoc Hon H, Minh Khoi L et al. (2025), JMIR formative research, 9, e53483
BibTeX
@article{statusofdigital-2025/2,
title={Status of Digital Health Technology Adoption in 5 Vietnamese Hospitals: Cross-Sectional Assessment.},
author={Tran DM, Thanh Dung N, Minh Duc C, Ngoc Hon H, Minh Khoi L et al.},
journal={JMIR formative research},
volume={9},
number={ARTN e53483},
pages={e53483},
publisher={JMIR Publications},
year = "2025"
}
Individualised Treatment Effects Estimation with Composite Treatments and Composite Outcomes
Chauhan VK, Clifton L, Nigam G & Clifton DA (2025)
Aligning, autoencoding and prompting large language models for novel disease reporting
Liu F, Wu X, Huang J, Yang B, Branson K et al. (2025), IEEE Transactions on Pattern Analysis and Machine Intelligence, 47(5), 3332-3343
BibTeX
@article{aligningautoenc-2025/1,
title={Aligning, autoencoding and prompting large language models for novel disease reporting},
author={Liu F, Wu X, Huang J, Yang B, Branson K et al.},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume={47},
pages={3332-3343},
publisher={IEEE},
year = "2025"
}
Voice EHR: introducing multimodal audio data for health
Anibal J, Huth H, Li M, Hazen L, Daoud V et al. (2025), Frontiers in Digital Health, 6
Generative AI and unstructured audio data for precision public health.
Anibal J, Landa A, Nguyen H, Daoud V, Le T et al. (2025), npj health systems, 2(1), 19
SPIKELLM: SCALING UP SPIKING NEURAL NETWORK TO LARGE LANGUAGE MODELS VIA SALIENCY-BASED SPIKING
Xing X, Gao B, Liu Z, Clifton DA, Xiao S et al. (2025), 13th International Conference on Learning Representations Iclr 2025, 100615-100634
BibTeX
@inproceedings{spikellmscaling-2025/1,
title={SPIKELLM: SCALING UP SPIKING NEURAL NETWORK TO LARGE LANGUAGE MODELS VIA SALIENCY-BASED SPIKING},
author={Xing X, Gao B, Liu Z, Clifton DA, Xiao S et al.},
pages={100615-100634},
year = "2025"
}
Optimising Clinical Federated Learning through Mode Connectivity-based Model Aggregation
Thakur A, Molaei S, Schwab P, Belgrave D, Branson K et al. (2025), Proceedings of Machine Learning Research, 258, 163-171
BibTeX
@inproceedings{optimisingclini-2025/1,
title={Optimising Clinical Federated Learning through Mode Connectivity-based Model Aggregation},
author={Thakur A, Molaei S, Schwab P, Belgrave D, Branson K et al.},
pages={163-171},
year = "2025"
}
Information Transfer Across Clinical Tasks via Adaptive Parameter Optimisation
Thakur A, Gal E, Molaei S, Gu X, Schwab P et al. (2025), Proceedings of Machine Learning Research, 258, 3367-3375
BibTeX
@inproceedings{informationtran-2025/1,
title={Information Transfer Across Clinical Tasks via Adaptive Parameter Optimisation},
author={Thakur A, Gal E, Molaei S, Gu X, Schwab P et al.},
pages={3367-3375},
year = "2025"
}
CC-SAM: SAM with Cross-Feature Attention and Context for Ultrasound Image Segmentation
Gowda SN & Clifton DA (2025), Lecture Notes in Computer Science, 15103, 108-124
The doctor will polygraph you now
Anibal J, Gunkel J, Awan S, Huth H, Nguyen H et al. (2024), npj Health Systems, 1(1)
RenAIssance: A Survey Into AI Text-to-Image Generation in the Era of Large Model.
Bie F, Yang Y, Zhou Z, Ghanem A, Zhang M et al. (2024), IEEE transactions on pattern analysis and machine intelligence, PP
Predicting individual patient and hospital-level discharge using machine learning
Wei J, Zhou J, Zhang Z, Yuan K, Gu Q et al. (2024), communications medicine, 4(1)
Property prediction of bio‐derived block copolymer thermoplastic elastomers using graph kernel methods
Williams C, Petersen SR, Marzagão DK, Gregory G, Huang Y et al. (2024), Angewandte Chemie, 137(2)
BibTeX
@article{propertypredict-2024/11,
title={Property prediction of bio‐derived block copolymer thermoplastic elastomers using graph kernel methods},
author={Williams C, Petersen SR, Marzagão DK, Gregory G, Huang Y et al.},
journal={Angewandte Chemie},
volume={137},
number={e202411097},
publisher={Wiley},
year = "2024"
}
Property Prediction of Bio-Derived Block Copolymer Thermoplastic Elastomers Using Graph Kernel Methods.
Williams CK, Petersen SR, Marzagão DK, Gregory GL, Huang Y et al. (2024), Angewandte Chemie (International ed. in English), e202411097
BibTeX
@article{propertypredict-2024/11,
title={Property Prediction of Bio-Derived Block Copolymer Thermoplastic Elastomers Using Graph Kernel Methods.},
author={Williams CK, Petersen SR, Marzagão DK, Gregory GL, Huang Y et al.},
journal={Angewandte Chemie (International ed. in English)},
pages={e202411097},
publisher={Wiley},
year = "2024"
}
The doctor will polygraph you now: ethical concerns with AI for fact-checking patients.
Anibal J, Gunkel J, Awan S, Huth H, Nguyen H et al. (2024), ArXiv
BibTeX
@article{thedoctorwillpo-2024/11,
title={The doctor will polygraph you now: ethical concerns with AI for fact-checking patients.},
author={Anibal J, Gunkel J, Awan S, Huth H, Nguyen H et al.},
journal={ArXiv},
year = "2024"
}
A Comparison of Representation Learning Methods for Medical Concepts in EHR Databases
Liu Z, Wu X, Yang Y & Clifton DA (2024), 1-1
BibTeX
@inproceedings{acomparisonofre-2024/11,
title={A Comparison of Representation Learning Methods for Medical Concepts in EHR Databases},
author={Liu Z, Wu X, Yang Y & Clifton DA},
booktitle={Proceedings of the 15th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics},
pages={1-1},
year = "2024"
}
Predicting future hospital antimicrobial resistance prevalence using machine learning
Vihta K-D, Pritchard E, Pouwels K, Hopkins S, Guy RL et al. (2024), Communications Medicine, 4(1)
BibTeX
@article{predictingfutur-2024/10,
title={Predicting future hospital antimicrobial resistance prevalence using machine learning},
author={Vihta K-D, Pritchard E, Pouwels K, Hopkins S, Guy RL et al.},
journal={Communications Medicine},
volume={4},
number={197},
publisher={Springer Nature},
year = "2024"
}
Knowledge abstraction and filtering based federated learning over heterogeneous data views in healthcare
Thakur A, Molaei S, Nganjimi PC, Soltan A, Schwab P et al. (2024), npj Digital Medicine, 7(1)
BibTeX
@article{knowledgeabstra-2024/10,
title={Knowledge abstraction and filtering based federated learning over heterogeneous data views in healthcare},
author={Thakur A, Molaei S, Nganjimi PC, Soltan A, Schwab P et al.},
journal={npj Digital Medicine},
volume={7},
number={283},
publisher={Nature Research},
year = "2024"
}
Knowledge abstraction and filtering based federated learning over heterogeneous data views in healthcare
Thakur A, Molaei S, Nganjimi P, Liu F, Soltan A et al. (2024), npj Digital Medicine, 7(1)
BibTeX
@article{knowledgeabstra-2024/10,
title={Knowledge abstraction and filtering based federated learning over heterogeneous data views in healthcare},
author={Thakur A, Molaei S, Nganjimi P, Liu F, Soltan A et al.},
journal={npj Digital Medicine},
volume={7},
number={283},
publisher={Springer Nature},
year = "2024"
}
Efficiency at scale: Investigating the performance of diminutive language models in clinical tasks.
Taylor N, Ghose U, Rohanian O, Nouriborji M, Kormilitzin A et al. (2024), Artificial intelligence in medicine, 157, 103002
BibTeX
@article{efficiencyatsca-2024/10,
title={Efficiency at scale: Investigating the performance of diminutive language models in clinical tasks.},
author={Taylor N, Ghose U, Rohanian O, Nouriborji M, Kormilitzin A et al.},
journal={Artificial intelligence in medicine},
volume={157},
pages={103002},
publisher={Elsevier},
year = "2024"
}
Mine yOur owN Anatomy: revisiting medical image segmentation with extremely limited labels
You C, Dai W, Liu F, Min Y, Dvornek NC et al. (2024), IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(12), 11136-11151
BibTeX
@article{mineyourownanat-2024/9,
title={Mine yOur owN Anatomy: revisiting medical image segmentation with extremely limited labels},
author={You C, Dai W, Liu F, Min Y, Dvornek NC et al.},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume={46},
pages={11136-11151},
publisher={IEEE},
year = "2024"
}
Generalizability assessment of AI models across hospitals in a low-middle and high income country
Yang J, Dung NT, Thach PN, Phong NT, Phu VD et al. (2024), Nature Communications, 15
BibTeX
@article{generalizabilit-2024/9,
title={Generalizability assessment of AI models across hospitals in a low-middle and high income country
},
author={Yang J, Dung NT, Thach PN, Phong NT, Phu VD et al.},
journal={Nature Communications},
volume={15},
number={8270},
publisher={Springer Nature},
year = "2024"
}
Generalizability assessment of AI models across hospitals in a low-middle and high income country
Yang J, Dung NT, Thach PN, Phong NT, Phu VD et al. (2024), Nature Communications, 15(1)
BibTeX
@article{generalizabilit-2024/9,
title={Generalizability assessment of AI models across hospitals in a low-middle and high income country},
author={Yang J, Dung NT, Thach PN, Phong NT, Phu VD et al.},
journal={Nature Communications},
volume={15},
number={8270},
publisher={Nature Research},
year = "2024"
}
Atrial fibrillation after cardiac surgery: identifying candidate predictors through a Delphi process.
Bedford J, Fields KG, Collins GS, Lip GYH, Clifton DA et al. (2024), BMJ open, 14(9), e086589
BibTeX
@article{atrialfibrillat-2024/9,
title={Atrial fibrillation after cardiac surgery: identifying candidate predictors through a Delphi process.},
author={Bedford J, Fields KG, Collins GS, Lip GYH, Clifton DA et al.},
journal={BMJ open},
volume={14},
pages={e086589},
publisher={BMJ},
year = "2024"
}