Showing 175 publications by Lei Clifton
When Text and Numbers Disagree: Evidence Arbitration in Large Language Models
Carletti M, Phillips E, Gustafsson FK, Palo P, Clifton L et al. (2026)
BibTeX
@misc{whentextandnumb-2026/8,
title={When Text and Numbers Disagree: Evidence Arbitration in Large Language Models},
author={Carletti M, Phillips E, Gustafsson FK, Palo P, Clifton L et al.},
year = "2026"
}
The FAIR Case for A Coherent Interoperability to support NHS 10 Year Health Plan
Tomlinson H, Beck T, Castillo FD, Clifton L, Cresswell K et al. (2026), Scientific Data
Development and validation of a multimodal artificial intelligence-based model for predicting post-prostatectomy treatment outcomes from baseline biparametric prostate magnetic resonance imaging
Simon BD, Akcicek E, Harmon SA, Clifton L, Thakur A et al. (2026), Diagnostic and Interventional Radiology
BibTeX
@article{developmentandv-2026/6,
title={Development and validation of a multimodal artificial intelligence-based model for predicting post-prostatectomy treatment outcomes from baseline biparametric prostate magnetic resonance imaging},
author={Simon BD, Akcicek E, Harmon SA, Clifton L, Thakur A et al.},
journal={Diagnostic and Interventional Radiology},
publisher={Galenos Yayinevi},
year = "2026"
}
Measuring Epistemic Resilience of LLMs Under Misleading Medical Context
Zhou H, Zou X, Wu J, Wu S, Yu J et al. (2026)
BibTeX
@misc{measuringepiste-2026/6,
title={Measuring Epistemic Resilience of LLMs Under Misleading Medical Context},
author={Zhou H, Zou X, Wu J, Wu S, Yu J et al.},
year = "2026"
}
Assessing the Importance of Variation in Diagnostic Coding Among the Three Countries in the UK Biobank
Clifton L, Liu W, Collister JA, Littlejohns TJ, Goldacre RR et al. (2026), Learning Health Systems, 10(3)
BibTeX
@article{assessingtheimp-2026/5,
title={Assessing the Importance of Variation in Diagnostic Coding Among the Three Countries in the UK Biobank},
author={Clifton L, Liu W, Collister JA, Littlejohns TJ, Goldacre RR et al.},
journal={Learning Health Systems},
volume={10},
number={e70083},
publisher={Wiley},
year = "2026"
}
Geometric Characterisation and Structured Trajectory Surrogates for Clinical Dataset Condensation
Nganjimi PC, Soltan A, Belgrave D, Clifton L, Clifton D et al. (2026)
Digital morphine: why AI scribes are symptomatic relief for a broken system
Segal B, Allen L, Fieggen J, Clifton D & Clifton L (2026), BMJ Digital Health & AI, 2(1)
BibTeX
@article{digitalmorphine-2026/3,
title={Digital morphine: why AI scribes are symptomatic relief for a broken system},
author={Segal B, Allen L, Fieggen J, Clifton D & Clifton L},
journal={BMJ Digital Health & AI},
volume={2},
number={e000030},
publisher={BMJ Publishing Group},
year = "2026"
}
Democratising clinical AI through dataset condensation for classical clinical models
Thakur A, Molaei S, Nganjimi PC, Fieggen J, Soltan AAS et al. (2026)
Clinical-R1: empowering large language models for faithful and comprehensive reasoning with clinical objective relative policy optimization
Gu B, Zhou H, Segal BM, Wu J, Cao Z et al. (2026), Proceedings of The Second AAAI Bridge Program on AI for Medicine and Healthcare, 317, 117-126
BibTeX
@inproceedings{clinicalrempowe-2026/3,
title={Clinical-R1: empowering large language models for faithful and comprehensive reasoning with clinical objective relative policy optimization},
author={Gu B, Zhou H, Segal BM, Wu J, Cao Z et al.},
booktitle={2nd AAAI Bridge Program on AI for Medicine and Healthcare (AIMedHealth 2026)},
pages={117-126},
year = "2026"
}
When to and when not to use machine learning in risk prediction models
Clifton L, Powell J, Clifton DA & Sheikh A (2026), The Lancet Digital Health, 8(2), 100954
Cardiac health assessment across scenarios and devices using a multimodal foundation model pretrained on data from 1.7 million individuals
Gu X, Tang W, Han J, Sangha V, Liu F et al. (2026), Nature Machine Intelligence, 8(2), 220-233
BibTeX
@article{cardiachealthas-2026/2,
title={Cardiac health assessment across scenarios and devices using a multimodal foundation model pretrained on data from 1.7 million individuals},
author={Gu X, Tang W, Han J, Sangha V, Liu F et al.},
journal={Nature Machine Intelligence},
volume={8},
pages={220-233},
publisher={Nature Research},
year = "2026"
}
Bridging the generalisation gap: synthetic data generation for multi-site clinical model validation
Segal B, Fieggen J, Clifton D & Clifton L (2025), 2025 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
BibTeX
@inproceedings{bridgingthegene-2025/12,
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"
}
Navigating severe class imbalance in population cohort data
Fieggen J, Segal B, Walker E, Thakur A, Butler C et al. (2025)
BibTeX
@inproceedings{navigatingsever-2025/12,
title={Navigating severe class imbalance in population cohort data},
author={Fieggen J, Segal B, Walker E, Thakur A, Butler C et al.},
booktitle={47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2025)},
year = "2025"
}
Clinical-R1: Empowering Large Language Models for Faithful and Comprehensive Reasoning with Clinical Objective Relative Policy Optimization
Gu B, Zhou H, Segal BM, Wu J, Cao Z et al. (2025)
Multimorbidity, disease clusters and risk of all-cause and cause-specific mortality: a population-based prospective cohort study
Littlejohns TJ, Liu W, Calvin CM, Clifton L, Collister JA et al. (2025), Scientific Reports, 15(1)
BibTeX
@article{multimorbidityd-2025/11,
title={Multimorbidity, disease clusters and risk of all-cause and cause-specific mortality: a population-based prospective cohort study},
author={Littlejohns TJ, Liu W, Calvin CM, Clifton L, Collister JA et al.},
journal={Scientific Reports},
volume={15},
number={41393},
publisher={Nature Research},
year = "2025"
}
DrAgent: empowering Large Language Models as medical agents for multi-hop medical reasoning
Liu F, Li Z, Zhou H, Yin Q, Yang J et al. (2025), Findings of the Association for Computational Linguistics: EMNLP 2025, 15656-15668
BibTeX
@inproceedings{dragentempoweri-2025/11,
title={DrAgent: empowering Large Language Models as medical agents for multi-hop medical reasoning},
author={Liu F, Li Z, Zhou H, Yin Q, Yang J et al.},
booktitle={30th Conference on Empirical Methods in Natural Language Processing (EMNLP 2025)},
pages={15656-15668},
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
Beyond correlations: the necessity and the challenges of causal AI
Chauhan VK, Dhami DS, Gao B, Wang X, Clifton L et al. (2025)
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
BibTeX
@article{amultimodalauto-2025/8,
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},
number={110579},
publisher={Elsevier},
year = "2025"
}
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"
}
Individualised treatment effects estimation with composite treatments and composite outcomes
Kumar Chauhan V, Clifton L, Nigam G & Clifton DA (2025), 2025 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 1-7
BibTeX
@inproceedings{individualisedt-2025/7,
title={Individualised treatment effects estimation with composite treatments and composite outcomes},
author={Kumar Chauhan V, Clifton L, Nigam G & Clifton DA},
booktitle={47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2025)},
pages={1-7},
year = "2025"
}
Transforming label-efficient decoding of healthcare wearables with self-supervised learning and “embedded” medical domain expertise
Gu X, Liu Z, Han J, Qiu J, Fang W et al. (2025), Communications Engineering, 4(1)
BibTeX
@article{transforminglab-2025/7,
title={Transforming label-efficient decoding of healthcare wearables with self-supervised learning and “embedded” medical domain expertise},
author={Gu X, Liu Z, Han J, Qiu J, Fang W et al.},
journal={Communications Engineering},
volume={4},
number={135},
publisher={Nature Research},
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"
}
Dysregulated immune proteins in plasma in the UK Biobank predict multiple myeloma 12 years before clinical diagnosis
Fieggen J, Thakur A, Butler C, Ramasamy K, Thakurta A et al. (2025), Blood Advances, 9(15), 3766-3770
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 C, Ramasamy K, Thakurta A et al.},
journal={Blood Advances},
volume={9},
pages={3766-3770},
publisher={American Society of Hematology},
year = "2025"
}
Implementation Framework for AI Deployment at Scale in Healthcare Systems
Adnan HS, Shidani A, Clifton L, Bankhead CR & Perera-Salazar R (2025), iScience, 112406
Bridging the Generalisation Gap: Synthetic Data Generation for Multi-Site Clinical Model Validation
Segal B, Fieggen J, Clifton D & Clifton L (2025)
Application of large language models in medicine
Liu F, Zhou H, Gu B, Zou X, Huang J et al. (2025), Nature Reviews Bioengineering, 3(6), 445-464
RiskAgent: Autonomous Medical AI Copilot for Generalist Risk Prediction
Liu F, Wu J, Zhou H, Gu X, Molaei S et al. (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"
}
Large language models are poor clinical decision-makers: a comprehensive benchmark
Liu F, Li Z, Zhou H, Yin Q, Yang J et al. (2024), Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 13696-13710
BibTeX
@inproceedings{largelanguagemo-2024/11,
title={Large language models are poor clinical decision-makers: a comprehensive benchmark},
author={Liu F, Li Z, Zhou H, Yin Q, Yang J et al.},
booktitle={Conference on Empirical Methods in Natural Language Processing (EMNLP 2024)},
pages={13696-13710},
year = "2024"
}
At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods
Mesinovic M, Wong XC, Rajahram GS, Citarella BW, Peariasamy KM et al. (2024), Scientific Reports, 14(1)
BibTeX
@article{atadmissionpred-2024/7,
title={At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods},
author={Mesinovic M, Wong XC, Rajahram GS, Citarella BW, Peariasamy KM et al.},
journal={Scientific Reports},
volume={14},
number={16387},
publisher={Nature Research},
year = "2024"
}
Figure 3 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al. (2024)
Supplementary Table S2 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al. (2024)
BibTeX
@misc{supplementaryta-2024/6,
title={Supplementary Table S2 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank},
author={Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al.},
year = "2024"
}
Supplementary Table S5 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al. (2024)
BibTeX
@misc{supplementaryta-2024/6,
title={Supplementary Table S5 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank},
author={Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al.},
year = "2024"
}
Supplementary Figure S3 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al. (2024)
BibTeX
@misc{supplementaryfi-2024/6,
title={Supplementary Figure S3 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank},
author={Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al.},
year = "2024"
}
Supplementary Table S1 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al. (2024)
BibTeX
@misc{supplementaryta-2024/6,
title={Supplementary Table S1 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank},
author={Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al.},
year = "2024"
}
Supplementary Figure S5 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al. (2024)
BibTeX
@misc{supplementaryfi-2024/6,
title={Supplementary Figure S5 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank},
author={Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al.},
year = "2024"
}
Supplementary Figure S2 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al. (2024)
BibTeX
@misc{supplementaryfi-2024/6,
title={Supplementary Figure S2 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank},
author={Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al.},
year = "2024"
}
Supplementary Figure S4 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al. (2024)
BibTeX
@misc{supplementaryfi-2024/6,
title={Supplementary Figure S4 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank},
author={Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al.},
year = "2024"
}
Data from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al. (2024)
Supplementary Table S7 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al. (2024)
BibTeX
@misc{supplementaryta-2024/6,
title={Supplementary Table S7 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank},
author={Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al.},
year = "2024"
}
Supplementary Table S9 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al. (2024)
BibTeX
@misc{supplementaryta-2024/6,
title={Supplementary Table S9 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank},
author={Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al.},
year = "2024"
}
Supplementary Table S3 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al. (2024)
BibTeX
@misc{supplementaryta-2024/6,
title={Supplementary Table S3 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank},
author={Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al.},
year = "2024"
}
Supplementary Table S9 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al. (2024)
BibTeX
@misc{supplementaryta-2024/6,
title={Supplementary Table S9 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank},
author={Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al.},
year = "2024"
}
Supplementary Table S7 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al. (2024)
BibTeX
@misc{supplementaryta-2024/6,
title={Supplementary Table S7 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank},
author={Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al.},
year = "2024"
}
Supplementary Table S6 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al. (2024)
BibTeX
@misc{supplementaryta-2024/6,
title={Supplementary Table S6 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank},
author={Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al.},
year = "2024"
}
Supplementary Table S3 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al. (2024)
BibTeX
@misc{supplementaryta-2024/6,
title={Supplementary Table S3 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank},
author={Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al.},
year = "2024"
}
Supplementary Table S2 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al. (2024)
BibTeX
@misc{supplementaryta-2024/6,
title={Supplementary Table S2 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank},
author={Collister JA, Liu X, Littlejohns TJ, Cuzick J, Clifton L et al.},
year = "2024"
}