Machine learning for the prediction of sepsis: a systematic review and meta-analysis of diagnostic test accuracy
LM Fleuren, TLT Klausch, CL Zwager… - Intensive care …, 2020 - Springer
Purpose Early clinical recognition of sepsis can be challenging. With the advancement of
machine learning, promising real-time models to predict sepsis have emerged. We …
machine learning, promising real-time models to predict sepsis have emerged. We …
[HTML][HTML] A systematic review of clinical decision support systems for antimicrobial management: are we failing to investigate these interventions appropriately?
Objectives Clinical decision support systems (CDSS) for antimicrobial management can
support clinicians to optimize antimicrobial therapy. We reviewed all original literature …
support clinicians to optimize antimicrobial therapy. We reviewed all original literature …
Creating an automated trigger for sepsis clinical decision support at emergency department triage using machine learning
Objective To demonstrate the incremental benefit of using free text data in addition to vital
sign and demographic data to identify patients with suspected infection in the emergency …
sign and demographic data to identify patients with suspected infection in the emergency …
Prediction of sepsis patients using machine learning approach: a meta-analysis
Study objective Sepsis is a common and major health crisis in hospitals globally. An
innovative and feasible tool for predicting sepsis remains elusive. However, early and …
innovative and feasible tool for predicting sepsis remains elusive. However, early and …
A targeted real-time early warning score (TREWScore) for septic shock
Sepsis is a leading cause of death in the United States, with mortality highest among
patients who develop septic shock. Early aggressive treatment decreases morbidity and …
patients who develop septic shock. Early aggressive treatment decreases morbidity and …
A computational approach to early sepsis detection
JS Calvert, DA Price, UK Chettipally, CW Barton… - Computers in biology …, 2016 - Elsevier
Objective To develop high-performance early sepsis prediction technology for the general
patient population. Methods Retrospective analysis of adult patients admitted to the …
patient population. Methods Retrospective analysis of adult patients admitted to the …
[HTML][HTML] Integrating a machine learning system into clinical workflows: qualitative study
Background Machine learning models have the potential to improve diagnostic accuracy
and management of acute conditions. Despite growing efforts to evaluate and validate such …
and management of acute conditions. Despite growing efforts to evaluate and validate such …
[HTML][HTML] Shock index and early recognition of sepsis in the emergency department: pilot study
T Berger, J Green, T Horeczko, Y Hagar… - Western Journal of …, 2013 - ncbi.nlm.nih.gov
Methods: We performed a retrospective analysis of a cohort of adult ED patients at an
academic community trauma center with 95,000 annual visits, from February 1st, 2007 to …
academic community trauma center with 95,000 annual visits, from February 1st, 2007 to …
[HTML][HTML] The development an artificial intelligence algorithm for early sepsis diagnosis in the intensive care unit
Background Severe sepsis and septic shock are still the leading causes of death in Intensive
Care Units (ICUs), and timely diagnosis is crucial for treatment outcomes. The progression of …
Care Units (ICUs), and timely diagnosis is crucial for treatment outcomes. The progression of …
Development, implementation, and impact of an automated early warning and response system for sepsis
CA Umscheid, J Betesh… - Journal of hospital …, 2015 - Wiley Online Library
BACKGROUND Early recognition and timely intervention significantly reduce sepsis‐related
mortality. OBJECTIVE Describe the development, implementation, and impact of an early …
mortality. OBJECTIVE Describe the development, implementation, and impact of an early …