AIMC Topic: Sepsis

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A scoping review of machine learning for sepsis prediction- feature engineering strategies and model performance: a step towards explainability.

Critical care (London, England) May 28, 2024
BACKGROUND: Sepsis, an acute and potentially fatal systemic response to infection, significantly impacts global health by affecting millions annually. Prompt identification of sepsis is vital, as treatment delays lead to increased fatalities through ...
Sepsis Humans Machine Learning
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Screening and Identification of Neutrophil Extracellular Trap-related Diagnostic Biomarkers for Pediatric Sepsis by Machine Learning.

Inflammation May 25, 2024
Neutrophil extracellular trap (NET) is released by neutrophils to trap invading pathogens and can lead to dysregulation of immune responses and disease pathogenesis. However, systematic evaluation of NET-related genes (NETRGs) for the diagnosis of pe...
Biomarkers Sepsis Child, Preschool Peroxidase Humans Child Machine Learning Extracellular Traps Neutrophils
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A machine learning framework for interpretable predictions in patient pathways: The case of predicting ICU admission for patients with symptoms of sepsis.

Health care management science May 21, 2024
Proactive analysis of patient pathways helps healthcare providers anticipate treatment-related risks, identify outcomes, and allocate resources. Machine learning (ML) can leverage a patient's complete health history to make informed decisions about f...
Intensive Care Units Sepsis Critical Pathways Humans Neural Networks, Computer Machine Learning
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An interpretable machine learning model for predicting 28-day mortality in patients with sepsis-associated liver injury.

PloS one May 20, 2024
Sepsis-Associated Liver Injury (SALI) is an independent risk factor for death from sepsis. The aim of this study was to develop an interpretable machine learning model for early prediction of 28-day mortality in patients with SALI. Data from the Medi...
Female Male Humans Liver Diseases Risk Factors Middle Aged Machine Learning Aged Sepsis Prognosis
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Machine learning derived serum creatinine trajectories in acute kidney injury in critically ill patients with sepsis.

Critical care (London, England) May 10, 2024
BACKGROUND: Current classification for acute kidney injury (AKI) in critically ill patients with sepsis relies only on its severity-measured by maximum creatinine which overlooks inherent complexities and longitudinal evaluation of this heterogenous ...
Retrospective Studies Acute Kidney Injury Critical Illness Intensive Care Units Female Aged Humans Machine Learning Biomarkers Hospital Mortality Male Creatinine Middle Aged Sepsis
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Association between the stress hyperglycemia ratio and 28-day all-cause mortality in critically ill patients with sepsis: a retrospective cohort study and predictive model establishment based on machine learning.

Cardiovascular diabetology May 9, 2024
BACKGROUND: Sepsis is a severe form of systemic inflammatory response syndrome that is caused by infection. Sepsis is characterized by a marked state of stress, which manifests as nonspecific physiological and metabolic changes in response to the dis...
Predictive Value of Tests Cause of Death China Sepsis Blood Glucose Time Factors Hospital Mortality Hyperglycemia Male Middle Aged Risk Assessment Female Machine Learning Risk Factors Decision Support Techniques Aged Databases, Factual Humans Retrospective Studies Biomarkers Critical Illness Prognosis
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Improving sepsis classification performance with artificial intelligence algorithms: A comprehensive overview of healthcare applications.

Journal of critical care May 8, 2024
PURPOSE: This study investigates the potential of machine learning (ML) algorithms in improving sepsis diagnosis and prediction, focusing on their relevance in healthcare decision-making. The primary objective is to contribute to healthcare decision-...
Artificial Intelligence Machine Learning Algorithms Humans Sensitivity and Specificity Sepsis Bayes Theorem
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Establishment and Verification of an Artificial Intelligence Prediction Model for Children With Sepsis.

The Pediatric infectious disease journal May 8, 2024
BACKGROUND: Early identification of high-risk groups of children with sepsis is beneficial to reduce sepsis mortality. This article used artificial intelligence (AI) technology to predict the risk of death effectively and quickly in children with sep...
Humans Neural Networks, Computer Artificial Intelligence Retrospective Studies Child, Preschool Child Intensive Care Units, Pediatric Support Vector Machine Infant Sepsis Female Adolescent Infant, Newborn Male
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Can Machine Learning Personalize Cardiovascular Therapy in Sepsis?

Critical care explorations May 6, 2024
Large randomized trials in sepsis have generally failed to find effective novel treatments. This is increasingly attributed to patient heterogeneity, including heterogeneous cardiovascular changes in septic shock. We discuss the potential for machine...
Machine Learning Precision Medicine Sepsis Resuscitation Humans
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A Machine learning model for predicting sepsis based on an optimized assay for microbial cell-free DNA sequencing.

Clinica chimica acta; international journal of clinical chemistry May 4, 2024
OBJECTIVE: To integrate an enhanced molecular diagnostic technique to develop and validate a machine-learning model for diagnosing sepsis.
Male Middle Aged Sequence Analysis, DNA Prospective Studies Cell-Free Nucleic Acids Female Aged Sepsis Humans Machine Learning
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