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The aim of this study is the establishment of a warehouse physiological data and biomedical signal in intensive care adult patients in acute situations from particular records from the Philips Intellivue MP70 monitor.
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Cardiopulmonary failures are major public health concerns, due to the aging population. Each of these situations is burdened with a poor prognosis in the medium term and a source of prolonged hospitalizations, generating significant health costs. Early detection and prediction of organ failure could reduce health costs and risks for the patient, offering a reaction early and appropriate medical technology. The proposed approach aims to optimize the knowledge of a complex physiological domain and multi-system, while promoting the automatic transfer of knowledge. The approach proposed data-mining and development of algorithms for detecting and / or predicting a strong potential for disruption because it proposes to apply innovative automated analysis procedures to a fragile patient population, and then a transfer to the medical device industry.
From communicating tools of recording of the signals, the investigator envisage in a global way:
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Erwan L'Her, Professor
Data sourced from clinicaltrials.gov
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