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Discovery Sciences | What we say

Our thoughts, comments, progress, work in action and where we are talking.

Case Studies

Case study

Study on benefits of blood anticoagulants for heart failure patients

2020

Case study

Personalising heart failure treatment

2019

Case study

Improving stroke prediction

2019

Article

Realising the benefits of new healthcare technologies

December 5, 2018

Event

20-24 July 2020

3rd Interdisciplinary Signaling Workshop

July 20, 2020

Media

Dr Rabia Khan commenting on the future of personalised medicine at CSCHealth19

2020-01-14

Media

Overview of Clinical AI. Professor Lionel Tarassenko, Chairman of Sensyne Health's Scientific Advisory Board

2018-09-18

Publications

Our clinical AI expertise is underpinned by published articles in tier-one journals across multiple fields of AI and medical research.

IEEE Journal of Biomedical and Health Informatics

Gaussian Processes for Personalized Interpretable Volatilty Metrics in the Step-Down Ward

Bioinformatics

DeepAMR for Predicting Co-occurrent Resistance of Mycobacterium Tuberculosis

Contemporary Clinical Trials Communications

Comparing Different Ways of Calculating Sample Size for Two Independent Means: A Worked Example

2019

Gaussian Processes for Personalized Interpretable Volatilty Metrics in the Step-Down Ward

IEEE Journal of Biomedical and Health Informatics

Colopy, G.W., Roberts, S.J., and Clifton, D.A.

DeepAMR for Predicting Co-occurrent Resistance of Mycobacterium Tuberculosis

Bioinformatics

Yang, Y., Walker, T.M., Walker, A.S., Wilson, D.J., Peto, T.E.A., Crook, D.W., Shamout, F., CRyPTIC Consortium, Zhu, T.T., and Clifton, D.A.

Comparing Different Ways of Calculating Sample Size for Two Independent Means: A Worked Example

Contemporary Clinical Trials Communications

Clifton, L., Birks, J., and Clifton, D.A.

The Correlation Between Baseline Score and Post-intervention Score, and its Implications on Statistical Analysis

Trials

Clifton, L., Birks, J., and Clifton, D.A.

Unsupervised Bayesian Inference to Fuse Biosignal Sensory Estimates for Personalising Care

IEEE Journal of Biomedical and Health Informatics

Zhu, T.T., Pimentel, M.A.F.,Clifford, G.D., and Clifton, D.A.

2018

Estimation of Respiratory Rate from Motion Contaminated Photoplethysmography Signals Incorporating Accelerometry

Healthcare Technology Letters

Jarchi, D., Charlton, P., Pimentel, M., Casson, A., Tarassenko, L., and Clifton, D.A.

Estimation of Respiratory Rate from Motion-Contaminated Photoplethysmography Signals Incorporating Accelerometry

IET Healthcare Technology Letters

Jarchi, D., Charlton, P., Pimentel, M.A.F., Rodgers, S.J., Casson, A.J., Tarassenko, L., and Clifton, D.A.

Validation of Instantaneous Respiratory Rate using Reflectance PPG from Different Body Positions

Sensors

Jarchi, D., Salvi, D., Tarassenko, L., and Clifton, D.A.

Prediction of Susceptibility to First-Line Tuberculosis Drugs by DNA Sequencing

New England Journal of Medicine

Allix-Beguec, C., ..., Clifton, D.A., Yang, Y., ..., Zhu, B.

Smoothing Effect in Vital-Sign Recordings: Fact or Fiction? A Retrospective Cohort Analysis of Manual and Continuous Vital-Sign Measurements to Assess Data Smoothing in Post-Operative Care

Anesthesia and Analgesia

Tomlinson, H., Pimentel, M.A.F., Gerry, S., Clifton, D.A., Tarassenko, L., and Watkinson, P.J.

Predicting In-Hospital Mortality and Unanticipated Admissions to the Intensive Care Unit using Routinely Collected Blood Tests and Vital Signs: Development and Validation of a Multivariable Model

Resuscitation

Redfern, O.C., Pimentel, M.A.F., Prytherch, D., Meredith, P., Clifton, D.A., Tarassenko, L., Smith, G.B., and Watkinson, P.J.

Bayesian Fusion of Physiological Measurements using a Signal Quality Extension

Physiological Measurement

Zhu, T.T., Yang, Y., Johnson, A.E.W., Clifford, G.D., and Clifton, D.A.

Accelerometry-Based Estimation of Respiratory Rate for Post-Intensive Care Patient Monitoring

IEEE Sensors Journal

Jarchi, D., Rodgers, S.J., Tarassenko, L., and Clifton, D.A.

Accelerometry-Based Estimation of Respiratory Rate for Post-Intensive Care Patient Monitoring

IEEE Sensors Journal

Jarchi, D., Rodgers, S.J., Tarassenko, L., and Clifton, D.A.

Manual Centile-Based Early Warning Scores Derived from Statistical Distributions of Observational Vital-Sign Data

Resuscitation

Watkinson, P.J., Pimentel, M.A.F., Clifton, D.A., and Tarassenko, L.

Point Process Models for Novelty Detection on Spatial Point Patterns and their Extremes

Computational Statistics and Data Analysis

Luca, S., Pimentel, M.A.F., Watkinson, P.J., and Clifton, D.A.

Distributed Inference Condition Monitoring System for Rural Infrastructure in the Developing World

IEEE Sensors Journal

Greeff, H., Manandhar, A., Thomson, P., Hope, R., and Clifton, D.A.

Bayesian Optimisation of Personalised Models for Patient Vital-Sign Monitoring

IEEE Journal of Biomedical and Health Informatics

Colopy, G.W., Roberts, S.J., and Clifton, D.A.

Applied Machine Learning for the Prediction of Growth of Abdominal Aortic Aneurysm in Humans

European Journal of Vascular and Endovascular Surgery Short Reports

Lee, R., Jarchi, D., Perera, R., Jones, A., Cassimjee, I., Handa, A., and Clifton, D.A.

Application of Machine Learning Techniques to Tuberculosis Drug Resistance Analysis

Bioinformatics

Kouchaki, S., Yang, Y., Walker, T.M., Walker, S., Wilson, D.J., Peto, T.E.A., Crook, D.W., and Clifton, D.A.

A Robust Fusion Model for Estimating Respiratory Rate from Photoplethysmography and Electrocardiography

IEEE Transactions on Biomedical Engineering

Birrenkott, D.A., Pimentel, M.A.F., Watkinson, P.J., and Clifton, D.A.

Component Isolation for Multi-component Signal Analysis using a Non-parametric Gaussian Latent Feature Model

Mechanical Systems and Signal Processing

Yang, Y., Peng, Z., Dong, X., Zhang, W., and Clifton, D.A.

Machine Learning for Classifying Tuberculosis Drug-Resistance from DNA Sequencing Data

Bioinformatics

Yang, Y., Niehaus, K.E., Walker, T.M., Iqbal, Z., Walker, A.S., Wilson, D.J., Peto, T.E.A., Crook, D.W., and Clifton, D.A.

Bayesian Gaussian Processes for Identifying the Deteriorating Patient

Thesis submitted to the Department of Engineering Science, University of Oxford

Colopy, G.W.

A Robust Fusion Model for Estimating Respiratory Rate from Photoplethysmography and Electrocardiography

IEEE Transactions on Biomedical Engineering

Birrenkott, D.A., Pimentel, M.A.F., Watkinson, P.J., and Clifton, D.A.

Profiling the Propagation of Error from PPG to HRV Features in a Wearable Physiological-Monitoring Device

IET Healthcare Technology Letters

Morelli, D., Bartolini, L., Colombo, M., Plans, D., and Clifton, D.A.

Breathing Rate Estimation from the Electrocardiogram and Photoplethysmogram: A Review

IEEE Reviews in Biomedical Engineering

Charlton, P.H., Birrenkott, D.A., Bonnici, T., Pimentel, M.A.F., Johnson, A.E.W., Alastruey, J., Tarassenko, L., Watkinson, P.J., Beale, R., and Clifton D.A.

2017

Towards a Robust Estimation of Respiratory Rate from Pulse Oximeters

IEEE Transactions on Biomedical Engineering

Pimentel, M.A.F., Johnson, A.E.W., Charlton, P.H., Birrenkott, D.A., Watkinson, P.J., Tarassenko, L., and Clifton, D.A.

Extraction of Respiratory Signals from the Electrocardiogram and Photoplethysmogram: Technical and Physiological Determinants

Physiological Measurement

Charlton, P.H., Bonnici, T., Tarassenko, L., Alastruey, J., Clifton D.A., Beale, R., and Watkinson, P.J.

Accidental Infrastructure for Groundwater Monitoring in Africa

Environmental Modelling and Software

Colchester, F.E., Marais, H.G., Thomson, P., Hope, R., and Clifton, D.A.

Implementing an Electronic Observation and Early Warning Score Chart in the Emergency Department: A Feasibility Study

European Journal of Emergency Medicine

Pullinger, R., Wilson, S., Way, R., Santos, M., Wong, D., Clifton, D.A., Birks, J., and Tarassenko, L.

Case Studies of Medical Monitoring Systems

Clifton, D.A.

Future Directions in Health Monitoring

Equipment Health Monitoring in Complex Systems

King, S., Mills, A., Kadirkamanathan, V., and Clifton, D.A.

2016

Identifying Lineage Effects When Controlling for Population Structure Improves Power in Bacterial Association Studies

Nature Microbiology

Earle, S.G., Wu, C-H., Charlesworth, J., Stoesser, N., Gordon, N.C., Walker, T.M., Spencer, C.C.A., Iqbal, Z., Clifton, D.A., Smith, E.G., Ismail, N., Llewelyn, M.J., Peto, T.E.A., Crook, D.W., McVean, G., Walker, A.S., and Wilson, D.J.

One-Class Classification of Point Patterns of Extremes

Journal of Machine Learning Research

Luca, S., Clifton, D.A., and Vanrumste, B.

Machine Learning and Decision Support in Critical Care

Proceedings of the IEEE

Johnson, A.E.W., Ghassemi, M.M., Nemati, S., Niehaus, K.E., Clifton, D.A., and Clifford, G.D.

Analysis of a Data Fusion System for Continuous Vital-Sign Monitoring in an Emergency Department

European Journal of Emergency Medicine

Wilson, S., Wong, D., Pullinger, R., Way, R., Clifton, D.A., and Tarassenko, L.

An Assessment of Algorithms for Estimation of Respiratory Rate from the Electrocardiogram and Photoplethysmogram

Physiological Measurements

Charlton, P.H., Bonnici, T., Tarassenko, L., Clifton D.A., Beale, R., and Watkinson, P.J.

Machine Learning for Chronic Disease

IET Press

Niehaus, K.E. and Clifton, D.A.

Predicting Antibiotic Resistance from Genomic Data

IET Press

Yang, Y., Niehaus, K.E., and Clifton, D.A.

A Bayesian Model for Fusing Biomedical Labels

IET Press

Zhu, T.T., Clifford, G.D., and Clifton, D.A.

Machine Learning for Healthcare Technologies: An Introduction

IET

Clifton, D.A.

Whole-Genome Sequencing for Prediction of Mycobacterium Tuberculosis Drug-Susceptibility and Resistance: A Retrospective Cohort Study

Lancet Infectious Diseases

Walker, T.M., Kohl, T.A., Omar, S.V., Hedge, J., Del Oio Elias, C., Bradley, P., Iqbal, Z., Feuerriegel, S., Niehaus, K.E., Wilson, D.J., Clifton, D.A., Kapatai G., Ip, C., Bowden, R., Drobniewski, F., Allix-Beguec, C., Gaudin, C., Parkhill, J., Diel, R., Supply, P., Crook, D., Smith, E.G., Walker, A.S., Ismail, N., Nieman, S., and Peto, T.E.A.

2015

Multi-task Gaussian Processes for Multivariate Physiological Time-Series Analysis

IEEE Transactions on Biomedical Engineering

Duerichen, R., Pimentel, M.A.F., Clifton, L., Schweikard, A., and Clifton, D.A.

"Errors" and Omissions in Paper-Based Early Warning Scores: The Association with Changes in Vital Signs - A Database Analysis.

British Medical Journal

Clifton, D.A., Clifton, L., Sandu, D.M., Smith, G.B., Tarassenko, L., Vollam, S., and Watkinson, P.J.

Signal Quality Indices for the Electrocardiogram and Photoplethysmogram: Derivation and Applications to Wireless Monitoring

IEEE Journal of Biomedical and Health Informatics

Orphanidou, C., Bonnici, T., Charlton, P., Clifton, D.A., Vallance, D., and Tarassenko, L.

Probabilistic Estimation of Respiratory Rate from Wearable Sensors

"Wearable Electronic Sensors", ed. Mukhopadhyay, S., Smart Sensors, Measurement and Instrumentation

Pimentel, M.A.F., Charlton, P.H., and Clifton, D.A.

Health Informatics via Machine Learning for the Clinical Management of Patients

Yearbook of Medical Informatics

Clifton, D.A., Niehaus, K.E., Charlton, P., and Colopy, G.W.

Intelligent Electronic Health Systems

CRC Press

Clifton, D.A., Pimentel, M.A.F., Niehaus, K., Clifton, L., Peto, T.E.A., Crook, D.W., and Watkinson, P.J.

Probabilistic Estimation of Respiratory Rate from Wearable Sensors

in "Wearable Electronic Sensors", ed. Mukhopadhyay, S., Smart Sensors, Measurement and Instrumentation

Pimentel, M.A.F., Charlton, P.H., and Clifton, D.A.

Fusing Continuous-Valued Medical Labels Using a Bayesian Model

Annals of Biomedical Engineering

Zhu, T.T., Dunkley, N., Behar, J., Clifton, D.A., and Clifford, G.D.

Novelty Detection in Jet Engine Vibration Spectra

Int. Journal of Condition Monitoring

Clifton, D.A. and Tarassenko, L.

A Non-invasive Method for Estimating Lung Function

Int. Journal of Condition Monitoring

Clifton, L., Clifton, D.A., Farmery, A.D., and Hahn, C.E.W.

2014

Predictive Monitoring of Mobile Patients by Combining Clinical Observations with Data from Wearable Sensors

IEEE Journal of Biomedical and Health Informatics

Clifton, L., Clifton, D.A., Pimentel, M.A.F., Watkinson, P.J., and Tarassenko, L.

Extending the Generalised Pareto Distribution for Novelty Detection in High-Dimensional Spaces

Journal of Signal Processing Systems

Clifton, D.A., Hugueny, S., Clifton, L., and Tarassenko, L.

A Review of Novelty Detection

Signal Processing

Pimentel, M.A.F., Clifton, D.A., Clifton, L., and Tarassenko, L.

Non-contact Video-Based Vital Sign Monitoring Using Ambient Light and Auto-regressive Models

Physiological Measurement

Tarassenko, L., Villarroel, M., Guazzi, A., Jorge, J., Clifton, D.A., and Pugh, C.

Probabilistic Novelty Detection with Support Vector Machines

IEEE Transactions on Reliability

Clifton, L., Clifton, D.A., Zhang, Y., Watkinson, P.J., Tarassenko, L., and Yin, H

An Extreme Function Theory for Novelty Detection

IEEE Journal of Selected Topics on Signal Processing

Clifton, D.A., Clifton, L., Hugueny, S., Wong, D., and Tarassenko, L.

2013

Gaussian Processes for Personalised e-Health Monitoring with Wearable Sensors

IEEE Transactions on Biomedical Engineering

Clifton, L., Clifton, D.A., Pimentel, M.A.F., Watkinson, P.J., and Tarassenko, L.

A Non-invasive Method for Estimating Cardiopulmonary Variables Using Breath-by-Breath Injection of Two Tracer Gases

IEEE Journal of Translational Engineering in Health and Medicine

Clifton, L., Clifton, D., Hahn, C.E.W., and Farmery, A.D.

Assessment of Lung Function Using a Non-invasive Oscillating Gas-Forcing Technique

Respiratory Physiology & Neurobiology

Clifton, L., Clifton, D., Hahn, C.E.W., and Farmery, A.D.

A Large-Scale Clinical Validation of an Integrated Monitoring System in the Emergency Department

http://www.robots.ox.ac.uk/~davidc/pubs/jbhi_ed.pdf

Clifton, D.A., Wong, D., Clifton, L., Pullinger, R., and Tarassenko, L.

Modelling Physiological Deterioration in Post-operative Patient Vital-Sign Data

Pimentel, M.A.F., Clifton, D.A., Clifton, L., Watkinson, P.J., and Tarassenko, L.

The Digital Patient

Clinical Medicine

Bonnici, T., Clifton, D.A., Watkinson, P.J., and Tarassenko, L.

Track and Trigger in an Emergency Department: an Observational Evaluation Study.

Emergency Medicine Journal

Wilson, S., Wong, D., Clifton, D.A., Fleming, S., Way, R., Pullinger, R., and Tarassenko, L.

2012

A Two-Class Approach to the Detection of Physiological Deterioration in Patient Vital Signs, with Clinical Label Refinement

IEEE Transactions on Information Technology in Biomedicine

Khalid, S., Clifton, D.A., Clifton, L.A., and Tarassenko, L.

Annual Review: Wireless Technology in Disease State Management and Medicine

Annual Review of Medicine

Clifford, G.D. and Clifton, D.A.

Photoplethysmographic Derivation of Respiratory Rate: A Review of Relevant Respiratory and Circulatory Physiology

Journal of Medical Engineering and Technology

Meredith, D., Clifton, D.A., Charlton, P., Brooks, J., Pugh, C.W., and Tarassenko, L.

2011

Semiconductor Wireless Technology for Chronic Disease Management

Electronics Letters

Tarassenko, L. and Clifton, D.A.

Centile-Based Early Warning Scores Derived from Statistical Distributions of Vital Signs

Resuscitation

Tarassenko, L., Clifton, D.A., Pinsky, M.R., Hravnak, M.T., Woods, J.R., and Watkinson, P.

Probabilistic Patient Monitoring with Multivariate, Multimodal Extreme Value Theory

Communications in Computer Science

Hugueny, S., Clifton, D.A., and Tarassenko, L.

Novelty Detection with Multivariate Extreme Value Statistics

Journal of Signal Processing Systems

Clifton, D.A., Hugueny, S., and Tarassenko, L.

2009

Probabilistic Approaches to Condition Monitoring of Aerospace Engines

IMechE Part G: Journal of Aerospace Engineering

King, S., Bannister, P.R., Clifton, D.A., and Tarassenko, L.

Novelty Detection

Encyclopaedia of Structural Health Monitoring

Tarassenko, L., Clifton, D.A., Bannister, P.R., King, S., and King, D.

2008

Automated Novelty Detection in Industrial Systems

Studies in Computational Intelligence

Clifton, D.A., Clifton, L., Bannister, P.R., and Tarassenko, L.

Disclaimer: Sensyne Health are not responsible for external website content.

Our thoughts, comments, progress, work in action and where we are talking.

Case Studies

Case study

Study on benefits of blood anticoagulants for heart failure patients

2020

Case study

Personalising heart failure treatment

2019

Case study

Improving stroke prediction

2019

Articles

Article

Realising the benefits of new healthcare technologies

December 5, 2018

Events

Event

20-24 July 2020

3rd Interdisciplinary Signaling Workshop

July 20, 2020

Media

Media

Dr Rabia Khan commenting on the future of personalised medicine at CSCHealth19

Media

Overview of Clinical AI. Professor Lionel Tarassenko, Chairman of Sensyne Health's Scientific Advisory Board

Publications

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