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Mashup Score: 1
Background Prognostication of neurological outcome in patients who remain comatose after cardiac arrest resuscitation is complex. Clinical variables, as well as biomarkers of brain injury, cardiac injury, and systemic inflammation, all yield some prognostic value. We hypothesised that cumulative information obtained during the first three days of intensive care could produce a reliable model for…
Source: Critical CareCategories: Critical Care, Latest HeadlinesTweet
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Mashup Score: 0Prediction of hypotension events with physiologic vital sign signatures in the intensive care unit - 3 year(s) ago
Even brief hypotension is associated with increased morbidity and mortality. We developed a machine learning model to predict the initial hypotension event among intensive care unit (ICU) patients and designed an alert system for bedside implementation. From the Medical Information Mart for Intensive Care III (MIMIC-3) dataset, minute-by-minute vital signs were extracted. A hypotension event was…
Source: Critical CareCategories: Critical Care, Latest HeadlinesTweet-
#CritCare #OpenAccess Clinically significant #hypotension events in #ICU patients can be predicted 1 h in advance: a predictive #machine_learning #model https://t.co/uFNRpMlsd5 #FOAMed #FOAMcc #BMC #ICU #Artificial_intelligence#prediction @jlvincen @ISICEM https://t.co/WMb7E7DcWC
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#CritCare #OA P. Andersson et al.: #Artificial_intelligence to predict #neurological_outcome in #coma patients after #cardiac_arrest #resuscitation https://t.co/xLO02kJ77h #FOAMed #FOAMcc #BMC #ICU #modelling #machine_learning #neural_network #algorithm @ISICEM @jlvincen https://t.co/clxWLn8RyI