L
Lionel Tarassenko
Researcher at University of Oxford
Publications - 419
Citations - 19351
Lionel Tarassenko is an academic researcher from University of Oxford. The author has contributed to research in topics: Artificial neural network & Vital signs. The author has an hindex of 67, co-authored 395 publications receiving 16265 citations. Previous affiliations of Lionel Tarassenko include National Institutes of Health & National Institute for Health Research.
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Journal Article
Using a mobile health application to support self-management in chronic obstructive pulmonary disease: A six-month cohort study eHealth/ telehealth/ mobile health systems, 'AC-63541e8b0e2a0d7170bcd513bb89d0cf
Maxine Hardinge,Heather Rutter,Carmelo Velardo,Syed Ahmar Shah,Veronika Williams,Lionel Tarassenko,Andrew Farmer +6 more
TL;DR: Findings from a six-month, clinical, cohort study of COPD patients’ use of a mobile telehealth based (mHealth) application provide evidence for integrating telehealth interventions with clinical care pathways to support self-management in COPD.
Journal Article
Neural Networks and Related Methods for Classification - Discussion
P Whittle,J Kay,David J. Hand,Lionel Tarassenko,Philip J. Brown,D. M. Titterington,Charles C. Taylor,W R Gilks,Frank Critchley,A J Mayne,G Wahba,S P Luttrell,A J Baczkowski,Kanti V. Mardia,L Breiman,W Buntine,C Chatfield,R D Deveaux,C J Darken,Lyle H. Ungar,R H Glendinning,Trevor Hastie,Robert Tibshirani,Geoffrey J. McLachlan,D Michie,Art B. Owen,D H Wolpert,B D Ripley +27 more
Proceedings ArticleDOI
Multi-Task Convolutional Neural Network for Patient Detection and Skin Segmentation in Continuous Non-Contact Vital Sign Monitoring
Sitthichok Chaichulee,Mauricio Villarroel,João Jorge,Carlos Arteta,Gabrielle Green,Kenny McCormick,Andrew Zisserman,Lionel Tarassenko +7 more
TL;DR: A multi-task convolutional neural network for detecting the presence of a patient and segmenting the patient’s skin regions is developed and can produce accurate results and is robust to changes in different skin tones, pose variations, lighting variations, and routine interaction of clinical staff.
Journal ArticleDOI
Novelty detection for the identification of abnormalities
TL;DR: The main aim of the paper is to introduce the concept of a neural network predictor as a model of normality, trained to predict an output value given a set of input patterns, all of which are acquired during normal operation.
Journal ArticleDOI
Gestation-Specific Vital Sign Reference Ranges in Pregnancy
Lauren J. Green,Lucy Mackillop,Dario Salvi,Rebecca M. Pullon,Lise Loerup,Lionel Tarassenko,Jude Mossop,Clare Edwards,Stephen Gerry,Jacqueline Birks,Rupert Gauntlett,Kate Harding,Lucy C Chappell,Peter J. Watkinson +13 more
TL;DR: The findings refute the existence of a clinically significant BP drop from 12 weeks of gestation, and present widely relevant, gestation-specific reference ranges for detecting abnormal BP, heart rate, respiratory rate, oxygen saturation and temperature during pregnancy.