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Identification of Patient Deterioration in Vital-Sign Data using One-Class Support Vector Machines.

, , , and . FedCSIS, page 125-131. (2011)

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Vital-sign Data Fusion Models for Post-operative Patients., , , , and . BIOSIGNALS, page 410-413. SciTePress, (2012)A Robust Fusion Model for Estimating Respiratory Rate From Photoplethysmography and Electrocardiography., , , and . IEEE Trans. Biomed. Eng., 65 (9): 2033-2041 (2018)Critical Care Health Informatics Collaborative (CCHIC): Data, tools and methods for reproducible research: A multi-centre UK intensive care database., , , , , , , , , and 4 other author(s). Int. J. Medical Informatics, (2018)Phenotyping Clusters of Patient Trajectories suffering from Chronic Complex Disease., , , and . CoRR, (2020)XMI-ICU: Explainable Machine Learning Model for Pseudo-Dynamic Prediction of Mortality in the ICU for Heart Attack Patients., , and . CoRR, (2023)Modelling physiological deterioration in post-operative patient vital-sign data., , , , and . Medical Biol. Eng. Comput., 51 (8): 869-877 (2013)Physiological trajectory of patients pre and post ICU discharge1., , , , , , and . EMBC, page 3160-3163. IEEE, (2014)Patient centred variables with univariate associations with unplanned ICU admission: a systematic review., , , , , and . BMC Medical Informatics Decis. Mak., 19 (1): 98:1-98:9 (2019)Point process models for novelty detection on spatial point patterns and their extremes., , , and . Comput. Stat. Data Anal., (2018)Wearables for continuous patient monitoring on COVID-19 isolation wards., , , and . BHI, page 1-4. IEEE, (2023)