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Poster communications

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

Nassim Sahki 1, 2 Anne Gégout-Petit 1, 2 Sophie Wantz-Mézières 1, 2
1 BIGS - Biology, genetics and statistics
Inria Nancy - Grand Est, IECL - Institut Élie Cartan de Lorraine
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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https://hal.inria.fr/hal-02392756
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Submitted on : Wednesday, December 4, 2019 - 10:21:55 AM
Last modification on : Monday, August 24, 2020 - 2:48:38 PM
Long-term archiving on: : Thursday, March 5, 2020 - 2:03:03 PM

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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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