AIMC Topic: Sepsis-Associated Encephalopathy

Clear Filters Showing 1 to 4 of 4 articles

Integrated multi omics and machine learning reveal mitochondrial immunometabolic networks in sepsis associated encephalopathy.

Scientific reports Sep 29, 2025
Sepsis-associated encephalopathy (SAE) is a major complication in intensive care units, characterized by diffuse brain dysfunction due to systemic inflammation. Despite advances in critical care medicine, SAE remains a key factor in poor patient outc...
Transcriptome Sepsis Gene Expression Profiling Mitochondria Sepsis-Associated Encephalopathy DNA, Mitochondrial Multiomics Cytokines Machine Learning Humans Brain Biomarkers
View on PubMed DOI

Early prediction of sepsis associated encephalopathy in elderly ICU patients using machine learning models: a retrospective study based on the MIMIC-IV database.

Frontiers in cellular and infection microbiology Apr 17, 2025
BACKGROUND: Sepsis associated encephalopathy (SAE) is prevalent among elderly patients in the ICU and significantly affects patient prognosis. Due to the symptom similarity with other neurological disorders and the absence of specific biomarkers, ear...
Male Humans Aged, 80 and over Female Machine Learning Sepsis-Associated Encephalopathy Databases, Factual Aged Prognosis Early Diagnosis Intensive Care Units Algorithms Sepsis Retrospective Studies
View on PubMed DOI

Identification of sepsis-associated encephalopathy biomarkers through machine learning and bioinformatics approaches.

Scientific reports Dec 30, 2024
Sepsis-associated encephalopathy (SAE) is common in septic patients, characterized by acute and long-term cognitive impairment, and is associated with higher mortality. This study aimed to identify SAE-related biomarkers and evaluate their diagnostic...
Sepsis-Associated Encephalopathy Sepsis Computational Biology Gene Regulatory Networks Machine Learning Biomarkers Humans
View on PubMed DOI

A machine learning-based prediction model for sepsis-associated delirium in intensive care unit patients with sepsis-associated acute kidney injury.

Renal failure Dec 1, 2025
Sepsis-associated acute kidney injury (SA-AKI) patients in the ICU often suffer from sepsis-associated delirium (SAD), which is linked to unfavorable outcomes. This research aimed to develop a machine learning-based model for early SAD prediction in ...
Logistic Models Decision Trees ROC Curve Bayes Theorem Delirium Area Under Curve Predictive Value of Tests Male Aged, 80 and over Sepsis Middle Aged Reproducibility of Results Aged Female Retrospective Studies Databases, Factual Intensive Care Units Acute Kidney Injury Sepsis-Associated Encephalopathy Humans Predictive Learning Models Machine Learning
View on PubMed DOI
Popular Topics
Recent Journals