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Graph representation learning based on deep generative gaussian mixture models
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SeroTracker-RoB: a decision rule-based algorithm for reproducible risk of bias assessment of seroprevalence studies.
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Improving Classification of Tetanus Severity for Patients in Low-Middle Income Countries Wearing ECG Sensors by Using a CNN-Transformer Network.
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Lu P. et al, (2022), IEEE transactions on bio-medical engineering, PP
Adversarial De-confounding in Individualised Treatment Effects Estimation
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Timeliness of reporting of SARS-CoV-2 seroprevalence results and their utility for infectious disease surveillance.
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COPER: Continuous Patient State Perceiver
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Chauhan VK. et al, (2022), 2022 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)
Spectrum Estimation of Heart Rate Variability Using Low-rank Matrix Completion
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Classification of Tetanus Severity in Intensive-Care Settings for Low-Income Countries Using Wearable Sensing.
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Genome-wide association studies of global Mycobacterium tuberculosis resistance to 13 antimicrobials in 10,228 genomes identify new resistance mechanisms
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Prognostic model for atrial fibrillation after cardiac surgery: a UK cohort study
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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.
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SARS-CoV-2 infection in Africa: a systematic review and meta-analysis of standardised seroprevalence studies, from January 2020 to December 2021.
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Machine Learning-Based Risk Stratification for Gestational Diabetes Management
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Sepsis Mortality Prediction Using Wearable Monitoring in Low-Middle Income Countries.
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Identification of undiagnosed atrial fibrillation using a machine learning risk prediction algorithm and diagnostic testing (PULsE-AI) in primary care: cost-effectiveness of a screening strategy evaluated in a randomized controlled trial in England.
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Incremental Trainable Parameter Selection in Deep Neural Networks
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Nowruz at SemEval-2022 Task 7: Tackling Cloze Tests with Transformers and Ordinal Regression
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Wearable Vital Signs Monitoring for Patients with Asthma: A Review
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Machine learning for chronic disease
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Machine learning for healthcare technologies - an introduction
Chapter
Clifton DA., (2016), Machine Learning for Healthcare Technologies, 1 - 6
Patient physiological monitoring with machine learning
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Pimentel MAF. and Clifton DA., (2016), Machine Learning for Healthcare Technologies, 111 - 125
Predicting antibiotic resistance from genomic data
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Yang Y. et al, (2016), Machine Learning for Healthcare Technologies, 203 - 226
Introduction
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Telemetry-based vital sign monitoring for ambulatory hospital patients
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Measurement of respiratory rate from the photoplethysmogram in chest clinic patients
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Clifton D. et al, (2007), Journal of Clinical Monitoring and Computing, 21, 55 - 61
Two-dimensional tool design for two-dimensional equilibrium electrochemical machining die-sinking using a numerical method
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An automated algorithm for determining respiratory rate by photoplethysmogram in children
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Wavelet transform reassignment and the use of low-oscillation complex wavelets
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A fully automated algorithm for the determination of respiratory rate from the photoplethysmogram
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An algorithm for the detection of individual breaths from the pulse oximeter waveform
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Wavelet-based analysis of heart-rate-dependent ECG features
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Stiles MK. et al, (2004), Annals of Noninvasive Electrocardiology, 9, 316 - 322
An integrated strategy for materials characterisation and process simulation in electrochemical machining
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Mount AR. et al, (2003), Journal of Materials Processing Technology, 138, 449 - 454
Characterization and representation of non-ideal effects in electrochemical machining
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Clifton D. et al, (2003), Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 217, 373 - 385
The electrochemical machining characteristics of stainless steels
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Mount AR. et al, (2003), Journal of the Electrochemical Society, 150
Using wavelet transform reassignment techniques for ECG characterisation
Conference paper
Clifton D. et al, (2003), Computers in Cardiology, 30, 581 - 584
Ultrasonic measurement of the inter-electrode gap in electrochemical machining
Journal article
Clifton D. et al, (2002), International Journal of Machine Tools and Manufacture, 42, 1259 - 1267
Nutrient availability and maize growth in a soil amended with earthworm casts from a South African indigenous species
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Clifton D. et al, (2002), Bioresource Technology, 84, 197 - 201
The use of a segmented tool for the analysis of electrochemical machining
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Mount AR. et al, (2001), Journal of Applied Electrochemistry, 31, 1213 - 1220
The effects of machined workpiece surface integrity on the fatigue life of γ-titanium aluminide
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Electrochemical machining of gamma titanium aluminide intermetallics
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Clifton D. et al, (2001), Journal of Materials Processing Technology, 108, 338 - 348