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Development and validation of a diagnostic model for early differentiation of sepsis and non-infectious SIRS in critically ill children - a data-driven approach using machine-learning algorithms.
Lamping, Florian; Jack, Thomas; Rübsamen, Nicole; Sasse, Michael; Beerbaum, Philipp; Mikolajczyk, Rafael T; Boehne, Martin; Karch, André.
Affiliation
  • Lamping F; Department of Epidemiology, Research Group Epidemiological and Statistical Methods (ESME), Helmholtz Centre for Infection Research, Inhoffenstr. 7, 38124, Braunschweig, Germany.
  • Jack T; Department for Pediatric Cardiology and Intensive Care Medicine, Hannover Medical School, 30625, Hannover, Germany.
  • Rübsamen N; German Center for Infection Research (DZIF), Hannover-Braunschweig site, 30625, Hannover, Germany.
  • Sasse M; Department for Pediatric Cardiology and Intensive Care Medicine, Hannover Medical School, 30625, Hannover, Germany.
  • Beerbaum P; Department of Epidemiology, Research Group Epidemiological and Statistical Methods (ESME), Helmholtz Centre for Infection Research, Inhoffenstr. 7, 38124, Braunschweig, Germany.
  • Mikolajczyk RT; Department for Pediatric Cardiology and Intensive Care Medicine, Hannover Medical School, 30625, Hannover, Germany.
  • Boehne M; Department for Pediatric Cardiology and Intensive Care Medicine, Hannover Medical School, 30625, Hannover, Germany.
  • Karch A; Department of Epidemiology, Research Group Epidemiological and Statistical Methods (ESME), Helmholtz Centre for Infection Research, Inhoffenstr. 7, 38124, Braunschweig, Germany.
BMC Pediatr ; 18(1): 112, 2018 03 15.
Article in En | MEDLINE | ID: mdl-29544449
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Algorithms / Decision Support Techniques / Systemic Inflammatory Response Syndrome / Machine Learning Type of study: Clinical_trials / Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limits: Adolescent / Child / Child, preschool / Female / Humans / Infant / Male / Newborn Language: En Journal: BMC Pediatr Journal subject: PEDIATRIA Year: 2018 Document type: Article Affiliation country: Alemania Country of publication: Reino Unido
Fulltext
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Algorithms / Decision Support Techniques / Systemic Inflammatory Response Syndrome / Machine Learning Type of study: Clinical_trials / Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limits: Adolescent / Child / Child, preschool / Female / Humans / Infant / Male / Newborn Language: En Journal: BMC Pediatr Journal subject: PEDIATRIA Year: 2018 Document type: Article Affiliation country: Alemania Country of publication: Reino Unido