Artificial Intelligence for End Tidal Capnography Guided Resuscitation: A Conceptual Framework

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dc.contributor.authorNassal, Michelle
dc.contributor.authorSugavanam, Nithin
dc.contributor.authorAramendi, Elisabete
dc.contributor.authorJaureguibeitia, Xabier
dc.contributor.authorElola, Andoni
dc.contributor.authorPanchal, Ashish
dc.contributor.authorUlintz, Alexander
dc.contributor.authorWang, Henry
dc.contributor.authorErtin, Emre
dc.date.accessioned2023-12-26T18:42:25Z
dc.date.available2023-12-26T18:42:25Z
dc.date.issued2024-01-03
dc.identifier.doi10.24251/HICSS.2024.471
dc.identifier.isbn978-0-9981331-7-1
dc.identifier.othere413140e-0613-4dbb-9782-e5f901bd99eb
dc.identifier.urihttps://hdl.handle.net/10125/106854
dc.language.isoeng
dc.relation.ispartofProceedings of the 57th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectTechnology, Machine Learning, and Bias in Emergency Care
dc.subjectartificial intelligence
dc.subjectcardiac arrest
dc.subjectend tidal capnography
dc.subjectreinforcement learning
dc.subjectresuscitation
dc.titleArtificial Intelligence for End Tidal Capnography Guided Resuscitation: A Conceptual Framework
dc.typeConference Paper
dc.type.dcmiText
dcterms.abstractArtificial Intelligence (AI) and machine learning have advanced healthcare by defining relationships in complex conditions. Out-of-hospital cardiac arrest (OHCA) is a medically complex condition with several etiologies. Survival for OHCA has remained static at 10% for decades in the United States. Treatment of OHCA requires the coordination of numerous interventions, including the delivery of multiple medications. Current resuscitation algorithms follow a single strict pathway, regardless of fluctuating cardiac physiology. OHCA resuscitation requires a real-time biomarker that can guide interventions to improve outcomes. End tidal capnography (ETCO2) is commonly implemented by emergency medical services professionals in resuscitation and can serve as an ideal biomarker for resuscitation. However, there are no effective conceptual frameworks utilizing the continuous ETCO2 data. In this manuscript, we detail a conceptual framework using AI and machine learning techniques to leverage ETCO2 in guided resuscitation.
dcterms.extent6 pages
prism.startingpage3898

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Technology, Machine Learning, and Bias in Emergency Care