AIMC Topic: Sepsis

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Development and application of an early prediction model for risk of bloodstream infection based on real-world study.

BMC medical informatics and decision making May 14, 2025
BACKGROUND: Bloodstream Infection (BSI) is a severe systemic infectious disease that can lead to sepsis and Multiple Organ Dysfunction Syndrome (MODS), resulting in high mortality rates and posing a major public health burden globally. Early identifi...
Aged Adult Male Middle Aged Machine Learning Algorithms Female Risk Assessment China Sepsis Early Diagnosis Humans
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Predictors and associations of complications in ureteroscopy for stone disease using AI: outcomes from the FLEXOR registry.

Urolithiasis May 14, 2025
We aimed to develop machine learning(ML) algorithms to evaluate complications of flexible ureteroscopy and laser lithotripsy(fURSL), providing a valid predictive model. 15 ML algorithms were trained on a large number fURSL data from > 6500 patients f...
Sepsis Registries Kidney Calculi Ureter Lithotripsy, Laser Ureteroscopy Ureteral Calculi Adult Male Middle Aged Postoperative Complications Algorithms Female Aged Humans Machine Learning
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Multicenter target trial emulation to evaluate corticosteroids for sepsis stratified by predicted organ dysfunction trajectory.

Nature communications May 13, 2025
Corticosteroids decrease the duration of organ dysfunction in sepsis and a range of overlapping and complementary infectious critical illnesses, including septic shock, pneumonia and the acute respiratory distress syndrome (ARDS). The risk and benefi...
Retrospective Studies Female Aged Pneumonia Male Middle Aged Humans Multiple Organ Failure Sepsis Machine Learning Organ Dysfunction Scores Shock, Septic Adrenal Cortex Hormones Respiratory Distress Syndrome
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Machine learning model to predict sepsis in ICU patients with intracerebral hemorrhage.

Scientific reports May 10, 2025
Patients with intracerebral hemorrhage (ICH) are highly susceptible to sepsis. This study evaluates the efficacy of machine learning (ML) models in predicting sepsis risk in intensive care units (ICUs) patients with ICH. We conducted a retrospective ...
Intensive Care Units Female Risk Factors Aged Machine Learning Prognosis Cerebral Hemorrhage Retrospective Studies Male Humans Middle Aged Sepsis Logistic Models
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Identification of Hub Genes and Key Pathways Associated with Sepsis Progression Using Weighted Gene Co-Expression Network Analysis and Machine Learning.

International journal of molecular sciences May 7, 2025
Sepsis is a life-threatening condition driven by dysregulated immune responses, resulting in organ dysfunction and high mortality rates. Identifying key genes and pathways involved in sepsis progression is crucial for improving diagnostic and therape...
Gene Ontology Disease Progression Gene Expression Profiling Transcriptome Humans Protein Interaction Maps Sepsis Machine Learning Gene Regulatory Networks Biomarkers Computational Biology Male Signal Transduction
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Comparison of different AI systems for diagnosing sepsis, septic shock, and cardiogenic shock: a retrospective study.

Scientific reports May 6, 2025
Sepsis, septic shock, and cardiogenic shock are life-threatening conditions associated with high mortality rates, but differentiating them is complex because they share certain symptoms. Using the Medical Information Mart for Intensive Care (MIMIC)-I...
Male Retrospective Studies Middle Aged Humans Shock, Septic Female Neural Networks, Computer Sepsis Bayes Theorem Aged Artificial Intelligence Shock, Cardiogenic Adult
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Generative AI mitigates representation bias and improves model fairness through synthetic health data.

PLoS computational biology May 1, 2025
Representation bias in health data can lead to unfair decisions and compromise the generalisability of research findings. As a consequence, underrepresented subpopulations, such as those from specific ethnic backgrounds or genders, do not benefit equ...
Humans Artificial Intelligence Female Male Sepsis Computational Biology Bias
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Study on the mechanism of action of the active ingredient of Calculus Bovis in the treatment of sepsis by integrating single-cell sequencing and machine learning.

Medicine Apr 18, 2025
BACKGROUND: Sepsis, a complex inflammatory condition with high mortality rates, lacks effective treatments. This study explores the therapeutic mechanisms of Calculus Bovis in sepsis using network pharmacology and RNA sequencing.
Machine Learning Single-Cell Analysis Humans Molecular Dynamics Simulation Protein Interaction Maps Molecular Docking Simulation Sequence Analysis, RNA Network Pharmacology China Drugs, Chinese Herbal Sepsis
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Screening of mitochondrial-related biomarkers connected with immune infiltration for acute respiratory distress syndrome through WGCNA and machine learning.

Medicine Mar 7, 2025
Septic acute respiratory distress syndrome (ARDS) is a complex and noteworthy type, but its molecular mechanism has not been fully elucidated. The aim is to explore specific biomarkers to diagnose sepsis-induced ARDS. Gene expression data of sepsis a...
Humans Machine Learning Biomarkers Gene Expression Profiling Sepsis Gene Regulatory Networks Nomograms Neutrophils Respiratory Distress Syndrome Mitochondria
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Identification of DNA damage repair-related genes in sepsis using bioinformatics and machine learning: An observational study.

Medicine Jan 31, 2025
Sepsis is a life-threatening disease with a high mortality rate, for which the pathogenetic mechanism still unclear. DNA damage repair (DDR) is essential for maintaining genome integrity. This study aimed to explore the role of DDR-related genes in t...
Nomograms DNA Damage Cell Cycle Proteins DNA Repair Sepsis ROC Curve Computational Biology Humans Machine Learning Biomarkers
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