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ECMO PAL: using deep neural networks for survival prediction in venoarterial extracorporeal membrane oxygenation

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Manage episode 404921929 series 3308934
Content provided by ESICM. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by ESICM or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

VA-ECMO outcome scores have been previously developed and used extensively for risk adjustment, patient prognostication, and quality control across time and centres. The limitation of such scores is the derivation by using traditional statistical methods which are not capable of covering the complexity of ECMO outcomes. The Extracorporeal Life Support Organization Member Centres have developed a study where they aimed to leverage a large international patient cohort to develop and validate an AI-driven tool for predicting in-hospital mortality of VA-ECMO. The tool was derived entirely from pre-ECMO variables, allowing for mortality prediction immediately after ECMO initiation.

To learn more about this study listen to the podcast.

  continue reading

74 episodes

Artwork
iconShare
 
Manage episode 404921929 series 3308934
Content provided by ESICM. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by ESICM or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

VA-ECMO outcome scores have been previously developed and used extensively for risk adjustment, patient prognostication, and quality control across time and centres. The limitation of such scores is the derivation by using traditional statistical methods which are not capable of covering the complexity of ECMO outcomes. The Extracorporeal Life Support Organization Member Centres have developed a study where they aimed to leverage a large international patient cohort to develop and validate an AI-driven tool for predicting in-hospital mortality of VA-ECMO. The tool was derived entirely from pre-ECMO variables, allowing for mortality prediction immediately after ECMO initiation.

To learn more about this study listen to the podcast.

  continue reading

74 episodes

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