From vital signs to clinical outcomes for patients with sepsis: a machine learning basis for a clinical decision support system.
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How to improve vital sign data quality for use in clinical decision support systems? A qualitative study in nine Swedish emergency departmentsOpportunities and challenges in developing risk prediction models with electronic health records data: a systematic review.A systems biology analysis of brain microvascular endothelial cell lipotoxicityComputerized Clinical Decision Support: Contributions from 2014.Creating an automated trigger for sepsis clinical decision support at emergency department triage using machine learningTriage sepsis alert and sepsis protocol lower times to fluids and antibiotics in the ED.Using what you get: dynamic physiologic signatures of critical illness.Precision diagnosis: a view of the clinical decision support systems (CDSS) landscape through the lens of critical care.Development and Validation of an Automated Sepsis Risk Assessment System.Outcome Prediction in Clinical Treatment Processes.Combining Biomarkers with EMR Data to Identify Patients in Different Phases of Sepsis.A targeted real-time early warning score (TREWScore) for septic shock.In support of 'usual' perioperative care.Early sepsis detection in critical care patients using multiscale blood pressure and heart rate dynamics.Derivation and validation of different machine-learning models in mortality prediction of trauma in motorcycle riders: a cross-sectional retrospective study in southern Taiwan.Delay Within the 3-Hour Surviving Sepsis Campaign Guideline on Mortality for Patients With Severe Sepsis and Septic Shock.Clinical Informatics Researcher's Desiderata for the Data Content of the Next Generation Electronic Health Record.Prediction of Incident Hypertension Within the Next Year: Prospective Study Using Statewide Electronic Health Records and Machine Learning.Multicentre validation of a sepsis prediction algorithm using only vital sign data in the emergency department, general ward and ICU.Interface, information, interaction: a narrative review of design and functional requirements for clinical decision support.Review article: Sepsis in the emergency department - Part 1: Definitions and outcomes.Opportunities and obstacles for deep learning in biology and medicine.Thinking Together: Modeling Clinical Decision-Support as a Sociotechnical System.
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P2860
From vital signs to clinical outcomes for patients with sepsis: a machine learning basis for a clinical decision support system.
description
article científic
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article scientifique
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articolo scientifico
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artigo científico
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bilimsel makale
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scientific article published on 19 August 2013
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vedecký článok
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vetenskaplig artikel
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videnskabelig artikel
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vědecký článek
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name
From vital signs to clinical o ...... nical decision support system.
@en
From vital signs to clinical o ...... nical decision support system.
@nl
type
label
From vital signs to clinical o ...... nical decision support system.
@en
From vital signs to clinical o ...... nical decision support system.
@nl
prefLabel
From vital signs to clinical o ...... nical decision support system.
@en
From vital signs to clinical o ...... nical decision support system.
@nl
P2093
P2860
P1476
From vital signs to clinical o ...... nical decision support system.
@en
P2093
Eren Gultepe
Hien Nguyen
Ilias Tagkopoulos
Jason Adams
Jeffrey P Green
Timothy Albertson
P2860
P304
P356
10.1136/AMIAJNL-2013-001815
P577
2013-08-19T00:00:00Z