A dual boundary classifier for predicting acute hypotensive episodes in critical care

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dc.contributor.authorBhattacharya, Sakyajiten
dc.contributor.authorHuddar, Vijayen
dc.contributor.authorRajan, Vaibhaven
dc.contributor.authorReddy, Chandan K.en
dc.contributor.departmentComputer Scienceen
dc.date.accessioned2019-06-05T13:02:46Zen
dc.date.available2019-06-05T13:02:46Zen
dc.date.issued2018-02-23en
dc.description.abstractAn Acute Hypotensive Episode (AHE) is the sudden onset of a sustained period of low blood pressure and is one among the most critical conditions in Intensive Care Units (ICU). Without timely medical care, it can lead to an irreversible organ damage and death. By identifying patients at risk for AHE early, adequate medical intervention can save lives and improve patient outcomes. In this paper, we design a novel dual-boundary classification based approach for identifying patients at risk for AHE. Our algorithm uses only simple summary statistics of past Blood Pressure measurements and can be used in an online environment facilitating real-time updates and prediction. We perform extensive experiments with more than 4,500 patient records and demonstrate that our method outperforms the previous best approaches of AHE prediction. Our method can identify AHE patients two hours in advance of the onset, giving sufficient time for appropriate clinical intervention with nearly 80% sensitivity and at 95% specificity, thus having very few false positives.en
dc.description.notesThis work was supported by the US National Science Foundation grants IIS-1646881 and IIS-1527827 (CR) and Xerox Research Center India (VR).en
dc.description.sponsorshipUS National Science Foundation [IIS-1646881, IIS-1527827]; Xerox Research Center Indiaen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1371/journal.pone.0193259en
dc.identifier.eissn1932-6203en
dc.identifier.issue2en
dc.identifier.othere0193259en
dc.identifier.pmid29474481en
dc.identifier.urihttp://hdl.handle.net/10919/89758en
dc.identifier.volume13en
dc.language.isoenen
dc.publisherPLOSen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.titleA dual boundary classifier for predicting acute hypotensive episodes in critical careen
dc.title.serialPLOS ONEen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.dcmitypeStillImageen

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