Change-point detection method for the prediction of dreaded events during online monitoring of lung transplant patients - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Poster Communications Year : 2019

Change-point detection method for the prediction of dreaded events during online monitoring of lung transplant patients

Abstract

Context • Survival after lung transplantation is about 80% at 1 year and 50% at 6 years. • The two main complications responsible for deaths in lung transplant patients are infection and/or rejection. Main objective • Test the monitoring of lung transplant patients by connected sensors ; • Propose a methodology for real-time prediction of a serious event (infection and/ or rejection) via the change-point detection in the evolution of the multivariate signals collected by these connected sensors.
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Dates and versions

hal-02392756 , version 1 (04-12-2019)

Identifiers

  • HAL Id : hal-02392756 , version 1

Cite

Nassim Sahki, Anne Gégout-Petit, Sophie Wantz-Mézières. Change-point detection method for the prediction of dreaded events during online monitoring of lung transplant patients. Annual PhD students conference IAEM Lorraine, APIL 2019, Dec 2019, Nancy, France. ⟨hal-02392756⟩
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