L
Louis Mayaud
Researcher at University of Oxford
Publications - 34
Citations - 594
Louis Mayaud is an academic researcher from University of Oxford. The author has contributed to research in topics: Population & Health care. The author has an hindex of 12, co-authored 34 publications receiving 475 citations. Previous affiliations of Louis Mayaud include Versailles Saint-Quentin-en-Yvelines University & French Institute of Health and Medical Research.
Papers
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Journal ArticleDOI
A Physiological Time Series Dynamics-Based Approach to Patient Monitoring and Outcome Prediction
Li-wei H. Lehman,Ryan P. Adams,Louis Mayaud,George B. Moody,Atul Malhotra,Roger G. Mark,Shamim Nemati +6 more
TL;DR: The results suggest that the discovered dynamics of vital sign time series may contain additional prognostic value beyond that of the baseline acuity measures, and can potentially be used as an independent predictor of outcomes in the ICU.
Journal ArticleDOI
A comparison of recording modalities of P300 event-related potentials (ERP) for brain-computer interface (BCI) paradigm
Louis Mayaud,Marco Congedo,A. Van Laghenhove,A. Van Laghenhove,David Orlikowski,David Orlikowski,M. Figère,E. Azabou,F. Cheliout-Heraut +8 more
TL;DR: This study does not recommend the use of one modality over another based on performance but suggests the choice should be made on more practical considerations such as the expected length of use, the availability of skilled labor for system setup and above all, the patient comfort.
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Dynamic data during hypotensive episode improves mortality predictions among patients with sepsis and hypotension
Louis Mayaud,Peggy S. Lai,Gari D. Clifford,Lionel Tarassenko,Leo Anthony Celi,Djillali Annane +5 more
TL;DR: Hospital mortality predictions based on dynamic variables surrounding a hypotensive event is a new approach to predicting prognosis that has good discrimination and calibration and offers additional predictive prognostic information beyond established ones.
Journal Article
Patient specific predictions in the intensive care unit using a Bayesian ensemble
Alistair E. W. Johnson,Nic Dunkley,Louis Mayaud,Athanasios Tsanas,Andrew A. Kramer,Gari D. Clifford +5 more
TL;DR: The proposed prediction model performs favourably on both the provided and hidden data sets (set A and set B), and has the potential to be used effectively for patient-specific predictions.
Journal ArticleDOI
A “datathon” model to support cross-disciplinary collaboration
Jerome Aboab,Leo Anthony Celi,Peter Charlton,Mengling Feng,Mohammad M. Ghassemi,Dominic C Marshall,Louis Mayaud,Tristan Naumann,Ned McCague,Kenneth E. Paik,Tom J. Pollard,Matthieu Resche-Rigon,Justin D. Salciccioli,David J. Stone +13 more
TL;DR: A “datathon’ or “hackathon” model is proposed in which participants with disparate, but potentially synergistic and complementary, knowledge and skills effectively combine to address questions faced by clinicians.