Professor
Tingting Zhu
BEng DPhil (Oxon) MSc
Associate Professor in AI for Digital Health
Non-Tutorial Fellow at Kellogg College
Royal Academy of Engineering Fellow
Stipendiary College Lecturer at Mansfield College
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All publications by Professor Zhu
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,  Phuc Hau N,  Thi Thu Huyen D,  Thi Le Thu H,  Van Duc T,  VITAL (Vietnam ICU Translational Applications Laboratory) Investigators ,  Minh Yen L,  Thwaites CL,  Paton C,  et al. (2025)
Uncertainty-Inspired Multi-Task Learning in Arbitrary Scenarios of ECG Monitoring
Wang X,  Gao H,  Ma C,  Zhu T,  Yang F,  Liu C,  Fu H,  et al. (2025)
Transformers and large language models are efficient feature extractors for electronic health record studies
Yuan K,  Yoon CH,  Gu Q,  Munby H,  Walker AS,  Zhu T,  Eyre DW,  et al. (2025)
A scalable federated learning solution for secondary care using low-cost microcomputing: privacy-preserving development and evaluation of a COVID-19 screening test in UK hospitals
Soltan AS,  Thakur A,  Yang J,  Chauhan A,  D'Cruz LG,  Dickson P,  Soltan MA,  Thickett DR,  Eyre DW,  Zhu T,  Clifton DA,  et al. (2024)
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,  Nguyen TT,  Cao VTC,  Ha THD,  Chung LTT,  Truong TN,  Nguyen Le Nhu T,  Dao KB,  Nguyen HV,  Khanh PNQ,  Le KTT,  Tran LHB,  Nhat PTH,  Tran DM,  Lam YM,  Thwaites CL,  Mcknight J,  Vinh Chau NV,  Van Nuil JI,  Vietnam ICU Translational Applications Laboratory (VITAL) ,  et al. (2024)
Medical records condensation: a roadmap towards healthcare data democratisation
Thakur A,  Wang Y,  Dong M,  Ma P,  Petridis S,  Shang L,  Zhu T,  Clifton D,  et al. (2024)
Decoding 2.3 million ECGs: interpretable deep learning for advancing cardiovascular diagnosis and mortality risk stratification
Lu L,  Zhu T,  Ribeiro AH,  Clifton L,  Zhao E,  Zhou J,  Ribeiro ALP,  Zhang Y-T,  Clifton DA,  et al. (2024)
Feasibility of wearable monitors to detect heart rate variability in children with hand, foot and mouth disease.
Nhan LNT,  Hung NT,  Khanh TH,  Hong NTT,  Ny NTH,  Nhu LNT,  Han DDK,  Zhu T,  Thanh TT,  Tadesse GA,  Clifton D,  Van Doorn HR,  Van Tan L,  Thwaites CL,  et al. (2024)
Student Loss: Towards the Probability Assumption in Inaccurate Supervision.
Zhang S,  Li J-Q,  Fujita H,  Li Y-W,  Wang D-B,  Zhu T-T,  Zhang M-L,  Liu C-Y,  et al. (2024)
Data encoding for healthcare data democratization and information leakage prevention
Thakur A,  Wang Y,  Armstrong J,  Zhu T,  Abrol V,  Clifton DA,  et al. (2024)
CliqueFluxNet: Unveiling EHR Insights with Stochastic Edge Fluxing and Maximal Clique Utilisation using Graph Neural Networks
Molaei S,  Bousejin NG,  Ghosheh GO,  Thakur A,  Chauhan VK,  Zhu T,  Clifton DA,  et al. (2024)
AutoNet-generated deep layer-wise convex networks for ECG classification
Shen Y,  Lu L,  Zhu T,  Wang X,  Clifton L,  Chen Z,  Clarke R,  Clifton D,  et al. (2024)
Temporal dynamics unleashed: elevating variational graph attention
Molaei S,  Niknam G,  Ghosheh G,  Chauhan VK,  Zare H,  Zhu T,  Pan S,  Clifton D,  et al. (2024)
Clinical evaluation of AI-assisted muscle ultrasound for monitoring muscle wasting in ICU patients
Nhat PTH,  Van Hao N,  Yen LM,  Anh NH,  Khiem DP,  Kerdegari H,  Phuong LT,  Hoang VT,  Ngoc NT,  Thu LNM,  Trung TN,  Pisani L,  Razavi R,  Yacoub S,  Van Vinh Chau N,  King AP,  Thwaites L,  Denehy L,  Gomez A,  et al. (2024)
Computer-aided prognosis of tuberculous meningitis combining imaging and non-imaging data
Canas LS,  Dong THK,  Beasley D,  Donovan J,  Cleary JO,  Brown R,  Thuong NTT,  Nguyen PH,  Nguyen HT,  Razavi R,  Ourselin S,  Thwaites GE,  Modat M,  et al. (2024)
CliqueFluxNet: Unveiling EHR Insights with Stochastic Edge Fluxing and Maximal Clique Utilisation Using Graph Neural Networks.
Molaei S,  Bousejin NG,  Ghosheh GO,  Thakur A,  Chauhan VK,  Zhu T,  Clifton DA,  et al. (2024)
Transformers and large language models are efficient feature extractors for electronic health record studies
Yuan K,  Yoon CH,  Gu Q,  Munby H,  Walker S,  Zhu T,  Eyre D,  et al. (2024)
Refined matrix completion for spectrum estimation of heart rate variability
Lu L,  Zhu T,  Tan Y,  Zhou J,  Yang J,  Clifton L,  Zhang Y-T,  Clifton DA,  et al. (2024)
Refined matrix completion for spectrum estimation of heart rate variability
Lu L,  Zhu T,  Tan Y,  Zhou J,  Yang J,  Clifton L,  Zhang Y-T,  Clifton DA,  et al. (2024)
Position: reinforcement learning in dynamic treatment regimes needs critical reexamination
Luo Z,  Pan Y,  Watkinson P,  Zhu T,  et al. (2024)
Benchmarking Large Language Models in Evidence-Based Medicine.
Li J,  Deng Y,  Sun Q,  Zhu J,  Tian Y,  Li J,  Zhu T,  et al. (2024)
A survey of few-shot learning for biomedical time series
Li C,  Denison T,  Zhu T,  et al. (2024)
Machine learning and clinician predictions of antibiotic resistance in Enterobacterales bloodstream infections.
Yuan K,  Luk A,  Wei J,  Walker AS,  Zhu T,  Eyre DW,  et al. (2024)
Are Time Series Foundation Models Ready for Vital Sign Forecasting in Healthcare?
Gu X,  Liu Y,  Mohsin Z,  Bedford J,  Thakur A,  Watkinson P,  Clifton L,  Zhu T,  Clifton DA,  et al. (2024)
Adversarial de-confounding in individualised treatment effects estimation
Kumar V,  Molaei S,  Hoque Tania M,  Thakur A,  Zhu T,  Clifton D,  et al. (2023)
BLOod Test Trend for cancEr Detection (BLOTTED): protocol for an observational and prediction model development study using English primary care electronic health records data
Virdee PS,  Bankhead C,  Koshiaris C,  Wright Drakesmith C,  Oke J,  Withrow D,  Swain S,  Collins K,  Chammas L,  Tamm A,  Zhu T,  Morris E,  Holt T,  Birks J,  Perera R,  Hobbs R,  Nicholson B,  et al. (2023)
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,  Hacker A,  Wright N,  Zhu T,  Clifton D,  Bennett D,  Guo Y,  Pei P,  Lv J,  Yu C,  Yang L,  Li L,  Lu Y,  Chen Z,  Cairns BJ,  Chen Y,  Clarke R,  et al. (2023)
Synthesizing Mixed-type Electronic Health Records using Diffusion Models
Ceritli T,  Ghosheh GO,  Chauhan VK,  Zhu T,  Creagh AP,  Clifton DA,  et al. (2023)
Uncertainties in the analysis of heart rate variability: a systematic review
Lu L,  Zhu T,  Morelli D,  Creagh A,  Liu Z,  Yang J,  Liu F,  Zhang Y-T,  Clifton D,  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,  Dickson P,  Soltan M,  Thickett D,  Eyre D,  Zhu T,  Clifton D,  et al. (2023)
Data Encoding For Healthcare Data Democratisation and Information Leakage Prevention
Zhu T,  Armstrong J,  Abrol V,  Wang Y,  Clifton D,  Thakur A,  et al. (2023)
A Large Language Modelling Deep Learning Framework for the Next Pandemic
Zhu T,  Wu X,  Yang B,  You C,  Wang C,  Lu L,  Liu Z,  Zheng Y,  Sun X,  Yang Y,  Clifton D,  Liu F,  et al. (2023)
DyVGRNN: DYnamic mixture variational graph recurrent neural networks
Niknam G,  Molaei S,  Zare H,  Pan S,  Jalili M,  Zhu T,  Clifton D,  et al. (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,  Thu LNM,  Phuong LT,  Duong HTH,  Thuy DB,  McBride A,  Xochicale M,  Schultz MJ,  Razavi R,  King AP,  Thwaites C,  Van Vinh Chau N,  Yacoub S,  Gomez A,  et al. (2023)
Improving diagnostics with deep forest applied to electronic health records
Khodadadi A,  Ghanbari Bousejin N,  Molaei S,  Kumar Chauhan V,  Zhu T,  Clifton D,  et al. (2023)
The 2023 wearable photoplethysmography roadmap.
Charlton PH,  Allen J,  Bailon R,  Baker S,  Behar JA,  Chen F,  Clifford GD,  Clifton DA,  Davies HJ,  Ding C,  Ding X,  Dunn J,  Elgendi M,  Ferdoushi M,  Franklin D,  Gil E,  Hassan MF,  Hernesniemi J,  Hu X,  Ji N,  Khan Y,  Kontaxis S,  Korhonen I,  Kyriacou PA,  Laguna P,  et al. (2023)
A Multimodal Large Language Modelling Deep Learning Framework for the Future Pandemic
Liu F,  Zhu T,  Wu X,  Yang B,  You C,  Wang C,  Lu L,  Liu Z,  Zheng Y,  Sun X,  Yang Y,  Clifton D,  et al. (2023)
A Framework For Motor Function Characterization in Autism Spectrum Disorder
Paulo JR,  Sousa T,  Perdiz J,  Leal N,  Menezes P,  Zhu T,  Pires G,  Castelo-Branco M,  et al. (2023)
External validation of AI models in health should be replaced with recurring local validation
Youssef A,  Pencina M,  Thakur A,  Zhu T,  Clifton D,  Shah NH,  et al. (2023)
Impact of stress hyperglycemia ratio on mortality in patients with critical acute myocardial infarction: insight from American MIMIC-IV and the Chinese CIN-II study
Liu J,  Zhou Y,  Huang H,  Liu R,  Kang Y,  Zhu T,  Wu J,  Gao Y,  Li Y,  Wang C,  Chen S,  Xie N,  Zheng X,  Meng R,  Liu Y,  Tan N,  Gao F,  et al. (2023)
Heart rate variability measured from wearable devices as a marker of disease severity in tetanus
Hai HB,  Cattrall JWS,  Hao NV,  Van HMT,  Thuy DB,  Nhat PTH,  Khanh PNQ,  Duong HTH,  Duong TD,  Lu P,  Phuong LT,  Greeff H,  Zhu T,  Yen LM,  Clifton D,  Thwaites CL,  et al. (2023)
A medical multimodal large language model for future pandemics
Liu F,  Zhu T,  Wu X,  Yang B,  You C,  Wang C,  Lu L,  Liu Z,  Zheng Y,  Sun X,  Yang Y,  Clifton L,  Clifton DA,  et al. (2023)
Intelligent electrocardiogram acquisition via ubiquitous photoplethysmography monitoring
Liu Z,  Zhu T,  Lu L,  Zhang Y-T,  Clifton DA,  et al. (2023)
Data Encoding For Healthcare Data Democratisation and Information Leakage Prevention
Thakur A,  Zhu T,  Abrol V,  Armstrong J,  Wang Y,  Clifton DA,  et al. (2023)
Optimal Wavelength Combinations for Resolving in-vivo Changes of Haemoglobin and Cytochrome-c-oxidase Concentrations with NIRS
Zhu T,  Faulkner S,  Madaan T,  Bainbridge A,  Price D,  Thomas D,  Cady E,  Robertson N,  Golay X,  Tachtsidis I,  et al. (2023)
Medical records condensation: a roadmap towards healthcare data democratisation
Wang Y,  Thakur A,  Dong M,  Ma P,  Petridis S,  Shang L,  Zhu T,  Clifton DA,  et al. (2023)
All models are local: time to replace external validation with recurrent local validation
Youssef A,  Pencina M,  Thakur A,  Zhu T,  Clifton D,  Shah NH,  et al. (2023)
PN-QRS: An Uncertainty-aware QRS-complex Detection Method for Wearable ECGs
Wang X,  Gao H,  Ma C,  Cui C,  Zhu T,  Cheng X,  Li J,  Liu C,  et al. (2023)
Long-Term Enhancement of Brain Function and Cognition Using Cognitive Training and Brain Stimulation
Snowball A,  Tachtsidis I,  Popescu T,  Thompson J,  Delazer M,  Zamarian L,  Zhu T,  Cohen Kadosh R,  et al. (2022)
Real-world evaluation of AI driven COVID-19 triage for emergency admissions: External validation & operational assessment of lab-free and high-throughput screening solutions
Soltan A,  Yang J,  Pattanshetty R,  Novak A,  Yang Y,  Rohanian O,  Beer S,  Soltan M,  Thickett D,  Fairhead R,  Zhu T,  Eyre D,  Clifton D,  et al. (2022)
Digital health policy and programs for hospital care in Vietnam: scoping review
Tran DM,  Thwaites CL,  Van Nuil JI,  McKnight J,  Luu AP,  Paton C,  et al. (2022)
Real-world evaluation of rapid and laboratory-free COVID-19 triage for emergency care: external validation and pilot deployment of artificial intelligence driven screening
Soltan AAS,  Yang J,  Pattanshetty R,  Novak A,  Yang Y,  Rohanian O,  Beer S,  Soltan MA,  Thickett DR,  Fairhead R,  Zhu T,  Eyre DW,  Clifton DA,  et al. (2022)
Development, validation and comparison of multivariable risk scores for prediction of total stroke and stroke types in Chinese adults: a prospective study of 0.5 million adults
Chun M,  Clarke R,  Zhu T,  Clifton D,  Bennett DA,  Chen Y,  Guo Y,  Pei P,  Lv J,  Yu C,  Yang L,  Li L,  Chen Z,  Cairns BJ,  et al. (2022)
A crowd of BashTheBug volunteers reproducibly and accurately measure the minimum inhibitory concentrations of 13 antitubercular drugs from photographs of 96-well broth microdilution plates
Fowler P,  Wright C,  Spiers H,  Zhu T,  Baeten E,  Hoosdally S,  Cruz ALG,  Roohi A,  Kouchaki S,  Walker T,  Peto T,  Miller G,  Lintott C,  Clifton D,  Crook D,  Walker AS,  et al. (2022)
Sepsis mortality prediction using wearable monitoring in low-middle income countries
Ghiasi S,  Zhu T,  Lu P,  Hagenah J,  Khanh PNQ,  Hao NV,  Vital Consortium ,  Thwaites L,  Clifton DA,  et al. (2022)
Classification of tetanus severity in intensive-care settings for low-income countries using wearable sensing
Lu P,  Ghiasi S,  Hagenah J,  Hai HB,  Hao NV,  Khanh PNQ,  Khoa LDV,  Thwaites L,  Clifton DA,  Zhu T,  et al. (2022)
RapiD_AI: A framework for Rapidly Deployable AI for novel disease & pandemic preparedness
Youssef A,  Zhu T,  Thakur A,  Watkinson P,  Horby P,  Eyre D,  Clifton D,  et al. (2022)
Incremental trainable parameter selection in deep neural networks
Thakur A,  Abrol V,  Sharma P,  Zhu T,  Clifton DA,  et al. (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,  Thwaites L,  Clifton DA,  et al. (2022)
Spectrum estimation of heart rate variability using low-rank matrix completion
Lu L,  Zhu T,  Zhang Y-T,  Clifton DA,  et al. (2022)
RapiD_AI: A framework for Rapidly Deployable AI for novel disease & pandemic preparedness
Youssef A,  Zhu T,  Thakur A,  Watkinson P,  Horby P,  Eyre D,  Clifton D,  et al. (2022)
Learning of cluster-based feature importance for electronic health record time-series
Aguiar H,  Santos M,  Watkinson P,  Zhu T,  et al. (2022)
SoQal: Selective Oracle Questioning for Consistency Based Active Learning of Cardiac Signals
Kiyasseh D,  Zhu T,  Clifton D,  et al. (2022)
Refined Matrix Completion for Spectrum Estimation of Heart Rate Variability
Lu L,  Zhu T,  Tan Y,  Zhou J,  Clifton L,  Zhang Y-T,  Clifton D,  et al. (2022)
BLOod Test Trend for cancEr Detection (BLOTTED): protocol for an observational and prediction model development study using English primary care electronic health records data
Virdee P,  Bankhead C,  Koshiaris C,  Drakesmith CW,  Oke J,  Withrow D,  Swain S,  Collins K,  Chammas L,  Tamm A,  Zhu T,  Morris E,  Holt T,  Birks J,  Perera R,  Hobbs FDR,  Nicholson B,  et al. (2022)
Machine learning in patient flow: a review
El-Bouri R,  Taylor T,  Youssef A,  Zhu T,  Clifton D,  et al. (2021)
Discriminant knowledge extraction from electrocardiograms for automated diagnosis of myocardial infarction
Tadesse GA,  Weldemariam K,  Javed H,  Liu Y,  Liu J,  Chen J,  Zhu T,  et al. (2021)
Stroke risk prediction using machine learning: a prospective cohort study of 0.5 million Chinese adults
Chun M,  Clarke R,  Cairns B,  Clifton D,  Bennett D,  Chen Y-P,  Guo Y,  Pei P,  Lv J,  Yu C,  Yang L,  Li L,  Chen Z-M,  Zhu T,  et al. (2021)
Vital sign monitoring using wearable devices in a Vietnamese intensive care unit
Van H,  Hao N,  Phan Nguyen Quoc K,  Hai H,  Khoa L,  Yen L,  Nhat P,  Hai Duong H,  Thuy D,  Zhu T,  Greeff H,  Clifton D,  Thwaites C,  et al. (2021)
CLOCS: contrastive learning of cardiac signals across space, time, and patients
Kiyasseh D,  Zhu T,  Clifton D,  et al. (2021)
Development and validation of early warning score systems for COVID-19 patients
Youssef A,  Kouchaki S,  Shamout F,  Armstrong J,  El-Bouri R,  Taylor T,  Birrenkott D,  Vasey B,  Soltan A,  Zhu T,  Clifton D,  Eyre D,  et al. (2021)
Utility of single versus sequential measurements of risk factors for prediction of stroke in Chinese adults
Chun M,  Clarke R,  Zhu T,  Clifton J,  Bennett D,  Chen Y-P,  Yang L,  Chen Z-M,  Cairns B,  et al. (2021)
BashTheBug: a crowd of volunteers reproducibly and accurately measure the minimum inhibitory concentrations of 13 antitubercular drugs from photographs of 96-well broth microdilution plates
Fowler P,  Wright C,  Spiers H,  Zhu T,  Baeten EML,  Hoosdally S,  Cruz ALG,  Roohi A,  Kouchaki S,  Walker T,  Peto TEA,  Miller G,  Lintott C,  Clifton D,  Crook D,  Walker S,  The Zooniverse Volunteer Community ,  The CRyPTIC Consortium ,  et al. (2021)
Coronary artery disease: optimal lipoprotein(a) for survival—lower is better? A large cohort with 43,647 patients
Liu J,  Liu L,  Wang B,  Chen S,  Liu B,  Liang J,  Huang H,  Li Q,  Lun Z,  Ying M,  Chen G,  Huang Z,  Xu D,  Yan X,  Zhu T,  Tadesse GA,  Tan N,  Chen J,  Liu Y,  et al. (2021)
Real-world evaluation of AI-driven COVID-19 triage for emergency admissions: External validation & operational assessment of lab-free and high-throughput screening solutions
Soltan A,  Yang J,  Pattanshetty R,  Novak A,  Yang Y,  Rohanian O,  Beer S,  Soltan M,  Thickett D,  Fairhead R,  Zhu T,  Eyre D,  Clifton D,  CURIAL Translational Collaborative ,  et al. (2021)
Let your heart speak in its mother tongue: Multilingual captioning of cardiac signals
Kiyasseh D,  Zhu T,  Clifton D,  et al. (2021)
Towards scheduling federated deep learning using meta-gradients for inter-hospital learning
el-Bouri R,  Zhu T,  Clifton D,  et al. (2021)
Publisher Correction: Utility of single versus sequential measurements of risk factors for prediction of stroke in Chinese adults.
Chun M,  Clarke R,  Zhu T,  Clifton D,  Bennett D,  Chen Y,  Guo Y,  Pei P,  Lv J,  Yu C,  Yang L,  Li L,  Chen Z,  Cairns BJ,  China Kadoorie Biobank Collaborative Group ,  et al. (2021)
DeepMI: Deep multi-lead ECG fusion for identifying myocardial infarction and its occurrence-time
Tadesse GA,  Javed H,  Weldemariam K,  Liu Y,  Liu J,  Chen J,  Zhu T,  et al. (2021)
Improving patient flow during infectious disease outbreaks using machine learning for real-time prediction of patient readiness for discharge
Bishop J,  Javed H,  EL-Bouri R,  Zhu T,  Taylor T,  Peto T,  Watkinson P,  Eyre D,  Clifton D,  et al. (2021)
CROCS: Clustering and revival of cardiac signals based on patient disease class, sex, and age
Kiyasseh D,  Zhu T,  Clifton D,  et al. (2021)
Artificial intelligence for mechanical ventilation: systematic review of design, reporting standards, and bias
Gallifant J,  Zhang J,  Del Pilar Arias Lopez M,  Zhu T,  Camporota L,  Celi LA,  Formenti F,  et al. (2021)
Small RNA profiling in Mycobacterium insights into stress adapt ability
Chen Y,  Zhai W,  Zhang K,  Zhu T,  Su L,  Bermudez L,  Chen H,  Guo A,  et al. (2021)
Multi-Modality Machine Learning Models to Predict Stroke and Atrial Fibrillation in Patients with Heart Failure
Zhou J,  Murugappan L,  Lu L,  Chou OHI,  Cheung BMY,  Tse G,  Zhu T,  et al. (2021)
Multi-modal diagnosis of infectious diseases in the developing world
Tadesse G,  Javed H,  Le Nguyen Thanh N,  Duong Ha Thi H,  Le Van T,  Thwaites L,  Clifton D,  Zhu T,  et al. (2020)
Severity detection tool for patients with infectious disease
Tadesse G,  Zhu T,  Le Nguyen Thanh N,  Thanh Hung N,  Duong HTH,  Huu Khanh T,  Van Quang P,  Duong Tran D,  Minh Yen L,  VAN DOORN HR,  Van Hao N,  Prince J,  Javed H,  Kiyasseh D,  Van Tan L,  Thwaites C,  Clifton D,  et al. (2020)
PlethAugment: GAN-based PPG augmentation for medical diagnosis in low-resource settings
Kiyasseh D,  Tadesse G,  Nhan LNT,  Tan LV,  Thwaites C,  ZHU T,  Clifton D,  et al. (2020)
Student-teacher curriculum learning via reinforcement learning: predicting hospital inpatient admission location
El-Bouri R,  Eyre D,  Watkinson P,  Zhu T,  Clifton D,  et al. (2020)
Artificial intelligence driven assessment of routinely collected healthcare data is an effective screening test for COVID-19 in patients presenting to hospital
Soltan AAS,  Kouchaki S,  Zhu T,  Kiyasseh D,  Taylor T,  Hussain Z,  Peto T,  Brent A,  Eyre D,  Clifton D,  et al. (2020)
Machine learning for clinical outcome prediction
Shamout F,  Zhu T,  Clifton DA,  et al. (2020)
Smartwatch data help detect COVID-19
Zhu T,  Watkinson P,  Clifton DA,  et al. (2020)
Rapid triage for COVID-19 using routine clinical data for patients attending hospital: development and prospective validation of an artificial intelligence screening test
Soltan AAS,  Kouchaki S,  Zhu T,  Kiyasseh D,  Taylor T,  Hussain ZB,  Peto T,  Brent AJ,  Eyre DW,  Clifton DA,  et al. (2020)
Development and Validation of Early Warning Score Systems for COVID-19 Patients
Youssef A,  Kouchaki S,  Shamout F,  Armstrong J,  El-Bouri R,  Taylor T,  Birrenkott D,  Vasey B,  Soltan A,  Zhu T,  Clifton D,  Eyre D,  et al. (2020)
DROPS: Deep Retrieval of Physiological Signals via Attribute-specific Clinical Prototypes
Zhu T,  et al. (2020)
PCPs: Patient Cardiac Prototypes
Zhu T,  et al. (2020)
Phenotyping Clusters of Patient Trajectories suffering from Chronic Complex Disease
Zhu T,  et al. (2020)
CLOCS: Contrastive Learning of Cardiac Signals
Zhu T,  et al. (2020)
SoQal: Selective Oracle Questioning in Active Learning
Zhu T,  et al. (2020)
ALPS: Active Learning via Perturbations
Zhu T,  et al. (2020)
CLOPS: Continual Learning of Physiological Signals
Zhu T,  et al. (2020)
ALPS: Active learning via perturbations
Kiyasseh D,  Zhu T,  Clifton DA,  et al. (2020)
CLOPS: Continual learning of physiological signals
Kiyasseh D,  Zhu T,  Clifton DA,  et al. (2020)
DROPS: Deep retrieval of physiological signals via attribute-specific clinical prototypes
Kiyasseh D,  Clifton DA,  Zhu T,  et al. (2020)
PCPs: Patient cardiac prototypes
Kiyasseh D,  Zhu T,  Clifton DA,  et al. (2020)
Phenotyping clusters of patient trajectories suffering from chronic complex disease
Aguiar H,  Santos M,  Watkinson P,  Zhu T,  et al. (2020)
SoQal: Selective Oracle Questioning in Active Learning
Kiyasseh D,  Zhu T,  Clifton DA,  et al. (2020)
Student-teacher curriculum learning via reinforcement learning: Predicting hospital inpatient admission location
El-Bouri R,  Eyre D,  Watkinson P,  Zhu T,  Clifton D,  et al. (2020)
Knowledge Discovery with Electrocardiography Using Interpretable Deep Neural Networks
Lu L,  Zhu T,  Ribeiro AH,  Clifton L,  Zhao E,  Ribeiro ALP,  Zhang Y-T,  Clifton DA,  et al. (2020)
Compare SGLT2I versus non-SGLT2I users in type-2 diabetic mellitus patients on GLP-1 receptor agonist: A population-based and machine learning causal inference analysis
Luo Z,  Chou OH-I,  Ng ZMW,  Chung CTS,  Chan JSK,  Chan RNC,  Lu L,  Zhu T,  Cheung BMY,  Liu T,  Tse G,  Zhou J,  et al. (2020)
DeepMI: Deep Multi-lead ECG Fusion for Identifying Myocardial Infarction and its Occurrence-time
Tadesse GA,  Javed H,  Liu Y,  Liu J,  Chen J,  Weldemariam K,  Zhu T,  et al. (2020)
PCPs: Patient Cardiac Prototypes
Kiyasseh D,  Zhu T,  Clifton DA,  et al. (2020)
CLOPS: Continual Learning of Physiological Signals
Kiyasseh D,  Zhu T,  Clifton DA,  et al. (2020)
Continuous-valued annotations aggregation for heart rate detection
Xie Y,  Li J,  Zhu T,  Liu C,  et al. (2019)
Patient-specific physiological monitoring and prediction using structured Gaussian processes
Zhu T,  Wright Colopy G,  Macewen C,  Niehaus K,  Yang Y,  Pugh C,  Clifton D,  et al. (2019)
Deep interpretable early warning system for the detection of clinical deterioration
Shamout F,  Zhu T,  Sharma P,  Watkinson PJ,  Clifton DA,  et al. (2019)
Heart rate variability as an indicator of autonomic nervous system disturbance in tetanus
Duong HTH,  Abebe Tadesse G,  Nhat PTH,  Van Hao N,  Prince J,  Duong TD,  Trung Kien T,  Van Tan L,  Pugh C,  Loan HT,  Van Vinh Chau N,  Minh YL,  Zhu T,  Clifton D,  Thwaites L,  et al. (2019)
Heart rate variability as an indicator of autonomic nervous system disturbance in tetanus
Duong HTH,  Tadesse GA,  Nhat PTH,  Hao NV,  Prince J,  Duong TD,  Kien TT,  Nhat LTH,  Tan LV,  Pugh C,  Loan HT,  Chau NVV,  Minh Yen L,  Zhu T,  Clifton D,  Thwaites L,  et al. (2019)
Cardiovascular disease diagnosis using cross-domain transfer learning
Tadesse G,  Zhu T,  Liu Y,  Zhou Y,  Chen J,  Tian M,  Clifton D,  et al. (2019)
Student-Teacher Curriculum Learning via Reinforcement Learning: Predicting Hospital Inpatient Admission Location
el-Bouri R,  Eyre D,  Watkinson P,  Zhu T,  Clifton DA,  et al. (2019)
Severity Detection Tool for Patients with Infectious Disease
Zhu T,  et al. (2019)
Severity detection tool for patients with infectious disease
Tadesse GA,  Zhu T,  Thanh NLN,  Hung NT,  Duong HTH,  Khanh TH,  Van Quang P,  Tran DD,  Yen LM,  Van Doorn HR,  Van Hao N,  Prince J,  Javed H,  Kiyasseh D,  Van Tan L,  Thwaites L,  Clifton DA,  et al. (2019)
Severity Detection Tool for Patients with Infectious Disease
Tadesse GA,  Zhu T,  Thanh NLN,  Hung NT,  Duong HTH,  Khanh TH,  Van Quang P,  Tran DD,  Yen L,  Van Doorn HR,  Van Hao N,  Prince J,  Javed H,  DaniKiyasseh ,  Van Tan L,  Thwaites L,  Clifton DA,  et al. (2019)
Machine learning for classifying tuberculosis drug-resistance from DNA sequencing data
Yang Y,  Niehaus KE,  Walker TM,  Iqbal Z,  Walker A,  Wilson DJ,  Peto TEA,  Crook DWM,  Smith EG,  Zhu T,  Clifton DA,  et al. (2018)
Unsupervised Bayesian inference to fuse biosignal sensory estimates for personalising care
Zhu TT,  Pimentel MAF,  Clifford G,  Clifton DA,  et al. (2018)
Bayesian fusion of physiological measurements using a signal quality extension
Zhu TT,  Johnson AEW,  Yang Y,  Clifford GD,  Clifton D,  et al. (2018)
A crowdsourcing-based topic model for service matchmaking in Internet of Things
Liu Y,  Du F,  Sun J,  Jiang Y,  He J,  Zhu T,  Sun C,  et al. (2018)
Likelihood-based artefact detection in continuously-acquired patient vital signs
Colopy GW,  Zhu T,  Clifton L,  Roberts SJ,  Clifton DA,  et al. (2017)
Personalised patient monitoring in haemodialysis using hierarchical Gaussian processes
Zhu T,  Colopy GW,  Pugh CW,  Clifton DA,  et al. (2017)
Drug resistance classification for Mycobacterium tuberculosis using multi-output model with stacked auto-encoders
Yang Y,  Clifton D,  et al. (2017)
Drug Resistance Classification for Mycobacterium tuberculosis using Multi-output Model with Stacked Auto-encoders
Yang Y,  Clifton D,  et al. (2017)
Evaluation of the fetal QT interval using non-invasive fetal ECG technology
Behar J,  Zhu T,  Oster J,  Niksch A,  Mah DY,  Chun T,  Greenberg J,  Tanner C,  Harrop J,  Sameni R,  Ward J,  Wolfberg AJ,  Clifford GD,  et al. (2016)
A Bayesian model for fusing biomedical labels
Zhu T,  Clifford GD,  Clifton DA,  et al. (2016)
Novel approach to documenting expert ECG interpretation using eye tracking technology: a historical and biographical representation of the late Dr Rory Childers in action.
Bond RR,  Kligfield PD,  Zhu T,  Finlay DD,  Drew B,  Guldenring D,  Breen C,  Clifford GD,  Wagner GS,  et al. (2015)
Novel approach to documenting expert ECG interpretation using eye tracking technology: A historical and biographical representation of the late Dr Rory Childers in action
Bond RR,  Kligfield PD,  Zhu T,  Finlay DD,  Drew B,  Guldenring D,  Breen C,  Clifford GD,  Wagner GS,  et al. (2015)
Fusing continuous-valued medical labels using a Bayesian Model
Zhu T,  Dunkley N,  Behar J,  Clifton D,  Clifford GD,  et al. (2015)
Fusing continuous-valued medical labels using a Bayesian model
Zhu T,  Dunkley N,  Behar J,  Clifton DA,  Clifford GD,  et al. (2015)
Bayesian fusion of algorithms for the robust estimation of respiratory rate from the photoplethysmogram
Zhu T,  Pimentel MAF,  Clifford GD,  Clifton DA,  et al. (2015)
Fusing Continuous-valued Medical Labels using a Bayesian Model
Zhu T,  Dunkley N,  Behar J,  Clifton DA,  Clifford GD,  et al. (2015)
Crowd-sourced annotation of ecg signals using contextual information.
Zhu T,  Johnson AEW,  Behar J,  Clifford GD,  et al. (2014)
Crowd-sourced annotation of ECG signals using contextual information
Zhu T,  Johnson AEW,  Behar J,  Clifford GD,  et al. (2014)
Assessing computerized eye tracking technology for gaining insight into expert interpretation of the 12-lead electrocardiogram: an objective quantitative approach.
Bond RR,  Zhu T,  Finlay DD,  Drew B,  Kligfield PD,  Guldenring D,  Breen C,  Gallagher AG,  Daly MJ,  Clifford GD,  et al. (2014)
Assessing computerized eye tracking technology for gaining insight into expert interpretation of the 12-lead electrocardiogram: An objective quantitative approach
Bond RR,  Zhu T,  Finlay DD,  Drew B,  Kligfield PD,  Guldenring D,  Breen C,  Gallagher AG,  Daly MJ,  Clifford GD,  et al. (2014)
An intelligent cardiac health monitoring and review system
Zhu T,  Osipov M,  Papastylianou T,  Oster J,  Clifton DA,  Clifford GD,  et al. (2014)
CrowdLabel: A Crowdsourcing Platform for Electrophysiology
Zhu T,  Behar J,  Papastylianou T,  Clifford GD,  et al. (2014)
A Scalable mHealth System for Noncommunicable Disease Management
Clifford GD,  Arteta C,  Zhu T,  Pimentel MAF,  Santos M,  Domingos J,  Maraci M,  Behar J,  Oster J,  et al. (2014)
Evaluation of the fetal QT interval using non-invasive fetal ECG technology
Behar J,  Wolfberg A,  Zhu T,  Oster J,  Niksch A,  Mah D,  Chun T,  Greenberg J,  Tanner C,  Harrop J,  Van Esbroeck A,  Alexander A,  McCarroll M,  Drake T,  Silber A,  Sameni R,  Ward J,  Clifford G,  et al. (2014)
Brain mitochondrial oxidative metabolism during and after cerebral hypoxia-ischemia studied by simultaneous phosphorus magnetic-resonance and broadband near-infrared spectroscopy.
Bainbridge A,  Tachtsidis I,  Faulkner SD,  Price D,  Zhu T,  Baer E,  Broad KD,  Thomas DL,  Cady EB,  Robertson NJ,  Golay X,  et al. (2014)
Long-term enhancement of brain function and cognition using cognitive training and brain stimulation.
Snowball A,  Tachtsidis I,  Popescu T,  Thompson J,  Delazer M,  Zamarian L,  Zhu T,  Cohen Kadosh R,  et al. (2013)
Noninvasive Fetal ECG: the PhysioNet/Computing in Cardiology Challenge 2013.
Silva I,  Behar J,  Sameni R,  Zhu T,  Oster J,  Clifford GD,  Moody GB,  et al. (2013)
Bayesian Voting of Multiple Annotators for Improved QT Interval Estimation
Zhu T,  Johnson AEW,  Behar J,  Clifford GD,  et al. (2013)
DeepAMR for predicting co-occurrent resistance of Mycobacterium tuberculosis
Yang Y,  Walker TM,  Walker AS,  Wilson DJ,  Peto TEA,  Crook DW,  Shamout F,  Zhu T,  Clifton DA,  et al. ()
Phenotyping Clusters of Patient Trajectories suffering from Chronic Complex Disease
Aguiar H,  Santos M,  Watkinson P,  Zhu T,  et al. ()
SoQal: Selective Oracle Questioning in Active Learning
Kiyasseh D,  Zhu T,  Clifton DA,  et al. ()
Student Loss: Towards the Probability Assumption in Inaccurate Supervision
Zhang S,  Li J,  Fujita H,  Li Y,  Wang D,  Zhu T,  Zhang M,  Liu C,  et al. ()