AIMC Topic: Sepsis-Associated Encephalopathy

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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...
Humans Machine Learning Algorithms Databases, Factual Prognosis Retrospective Studies Intensive Care Units Female Aged Aged, 80 and over Male Sepsis Early Diagnosis Sepsis-Associated Encephalopathy
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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...
Humans Machine Learning Biomarkers Sepsis Gene Regulatory Networks Computational Biology Sepsis-Associated Encephalopathy
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