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Publications

Development of an enhanced scoring system to predict ICU readmission or in-hospital death within 24 hours using routine patient data from two NHS Foundation Trusts

Pimentel MAF. et al, (2024), BMJ Open, 14, e074604 - e074604

Digital health technologies and machine learning augment patient reported outcomes to remotely characterise rheumatoid arthritis.

Creagh AP. et al, (2024), NPJ Digit Med, 7

AZD1222 effectiveness against severe COVID-19 in individuals with comorbidity or frailty: the RAVEN cohort study.

Meeraus W. et al, (2024), The Journal of infection

Tetanus Severity Classification in Low-Middle Income Countries through ECG Wearable Sensors and a 1D-Vision Transformer

Lu P. et al, (2024), BioMedInformatics, 4, 285 - 294

Acceptance and User Experiences of a Wearable Device for the Management of Hospitalized Patients in COVID-19-Designated Wards in Ho Chi Minh City, Vietnam: Action Learning Project.

Luu AP. et al, (2024), JMIR human factors, 11

Undertaking multi-centre randomised controlled trials in primary care: learnings and recommendations from the PULsE-AI trial researchers.

Pollock KG. et al, (2024), BMC primary care, 25

A medical multimodal large language model for future pandemics.

Liu F. et al, (2023), NPJ digital medicine, 6

Semi-Supervised Learning for Multi-Label Cardiovascular Diseases Prediction: A Multi-Dataset Study.

Zhou R. et al, (2023), IEEE transactions on pattern analysis and machine intelligence, PP

Heart Rate Variability Measured from Wearable Devices as a Marker of Disease Severity in Tetanus.

Hai HB. et al, (2023), The American journal of tropical medicine and hygiene

External validation of AI models in health should be replaced with recurring local validation.

Youssef A. et al, (2023), Nature medicine

A Stacked Long Short-Term Memory Approach for Predictive Blood Glucose Monitoring in Women with Gestational Diabetes Mellitus

Lu HY. et al, (2023), Sensors, 23, 7990 - 7990

2D-WinSpatt-Net: A Dual Spatial Self-Attention Vision Transformer Boosts Classification of Tetanus Severity for Patients Wearing ECG Sensors in Low- and Middle-Income Countries

Lu P. et al, (2023), Sensors, 23, 7705 - 7705

DyVGRNN: DYnamic mixture Variational Graph Recurrent Neural Networks

Niknam G. et al, (2023), Neural Networks, 165, 596 - 610

Algorithmic fairness and bias mitigation for clinical machine learning with deep reinforcement learning

Yang J. et al, (2023), Nature Machine Intelligence

Improving Diagnostics with Deep Forest Applied to Electronic Health Records

Khodadadi A. et al, (2023), Sensors, 23, 6571 - 6571

Clinical benefit of AI-assisted lung ultrasound in a resource-limited intensive care unit.

Nhat PTH. et al, (2023), Critical care (London, England), 27

Independent external validation of the QRISK3 cardiovascular disease risk prediction model using UK Biobank.

Parsons RE. et al, (2023), Heart (British Cardiac Society)

The 2023 wearable photoplethysmography roadmap.

Charlton PH. et al, (2023), Physiological measurement

A Brief Review of Hypernetworks in Deep Learning

Chauhan VK. et al, (2023)

Combining machine learning with Cox models to identify predictors for incident post-menopausal breast cancer in the UK Biobank

Liu X. et al, (2023), Scientific Reports, 13

Evaluation of awake prone positioning effectiveness in moderate to severe COVID-19

Truong NT. et al, (2023), Wellcome Open Research, 8, 235 - 235

Dynamic Inter-treatment Information Sharing for Heterogeneous Treatment Effects Estimation

Chauhan VK. 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 AAS. et al, (2023)

Bedaquiline and clofazimine resistance in Mycobacterium tuberculosis: an in-vitro and in-silico data analysis.

Sonnenkalb L. et al, (2023), The Lancet. Microbe, 4, e358 - e368

Uncertainties in the Analysis of Heart Rate Variability: A Systematic Review.

Lu L. et al, (2023), IEEE reviews in biomedical engineering, PP

An adversarial training framework for mitigating algorithmic biases in clinical machine learning

Yang J. et al, (2023), npj Digital Medicine, 6

Heterogeneity in diagnosis and prognosis of ischaemic stroke subtypes: 9-year follow-up of 22000 cases in Chinese adults.

Chun M. et al, (2023), Int J Stroke

On the Effectiveness of Compact Biomedical Transformers.

Rohanian O. et al, (2023), Bioinformatics

Development and Validation of a Machine Learning Wrist-worn Step Detection Algorithm with Deployment in the UK Biobank

Small SR. et al, (2023)

A distribution-based selective optimization method for eliminating periodic defects in harmonic signals

Xin Q-Y. et al, (2023), Mechanical Systems and Signal Processing, 185, 109781 - 109781

Graph representation learning based on deep generative gaussian mixture models

Niknam G. et al, (2023), Neurocomputing, 523, 157 - 169

A Large Language Modelling Deep Learning Framework for the Next Pandemic

Zhu T. et al, (2023)

Adversarial De-confounding in Individualised Treatment Effects Estimation

Chauhan VK. et al, (2023), Proceedings of Machine Learning Research, 206, 837 - 849

Data Encoding For Healthcare Data Democratisation and Information Leakage Prevention

Zhu T. et al, (2023)

Digital Health and Machine Learning Technologies for Blood Glucose Monitoring and Management of Gestational Diabetes

Lu HY. et al, (2023), IEEE Reviews in Biomedical Engineering

DuKA: A Dual-Keyless-Attention Model for Multi-modality EHR Data Fusion and Organ Failure Prediction

Liu Z. et al, (2023), IEEE Transactions on Biomedical Engineering

Intelligent Electrocardiogram Acquisition Via Ubiquitous Photoplethysmography Monitoring

Liu Z. et al, (2023), IEEE Journal of Biomedical and Health Informatics

MiniALBERT: Model Distillation via Parameter-Efficient Recursive Transformers

Nouriborji M. et al, (2023), EACL 2023 - 17th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference, 1153 - 1165

Multimodal Learning With Transformers: A Survey

Xu P. et al, (2023), IEEE Transactions on Pattern Analysis and Machine Intelligence

Patient Clustering for Vital Organ Failure Using ICD Code with Graph Attention

Liu Z. et al, (2023), IEEE Transactions on Biomedical Engineering

Self-Aware SGD: Reliable Incremental Adaptation Framework For Clinical AI Models

Thakur A. et al, (2023), IEEE Journal of Biomedical and Health Informatics, 1 - 11

SeroTracker-RoB: a decision rule-based algorithm for reproducible risk of bias assessment of seroprevalence studies.

Bobrovitz N. et al, (2023), Research synthesis methods

Using Bottleneck Adapters to Identify Cancer in Clinical Notes under Low-Resource Constraints

Rohanian O. et al, (2023), Proceedings of the Annual Meeting of the Association for Computational Linguistics, 62 - 78

Continuous Patient State Attention Models

Chauhan VK. et al, (2022)

Digital Omicron detection using unscripted voice samples from social media.

Anibal JT. et al, (2022), medRxiv

Global SARS-CoV-2 seroprevalence from January 2020 to April 2022: A systematic review and meta-analysis of standardized population-based studies.

Bergeri I. et al, (2022), PLoS medicine, 19

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. et al, (2022), Vaccines, 10

Improving Classification of Tetanus Severity for Patients in Low-Middle Income Countries Wearing ECG Sensors by Using a CNN-Transformer Network.

Lu P. et al, (2022), IEEE transactions on bio-medical engineering, PP

Adversarial De-confounding in Individualised Treatment Effects Estimation

Chauhan VK. et al, (2022)

Epidemiological cut-off values for a 96-well broth microdilution plate for high-throughput research antibiotic susceptibility testing ofM. tuberculosis

(2022), European Respiratory Journal, 60, 2200239 - 2200239

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