Critical Care

Sepsis

Latest AI and machine learning research in sepsis for healthcare professionals.

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Critical-Care Subcategories: Sepsis
Showing 2836-2856 of 7,154 articles
Utilizing Machine Learning Models to Predict Acute Kidney Injury in Septic Patients from MIMIC-III Database

Sepsis is a severe condition that causes the body to respond incorrectly to an infection. This react...

Prediction of the infecting organism in peritoneal dialysis patients with acute peritonitis using interpretable Tsetlin Machines

The analysis of complex biomedical datasets is becoming central to understanding disease mechanisms,...

Development and Prospective Implementation of a Large Language Model based System for Early Sepsis Prediction

Sepsis is a dysregulated host response to infection with high mortality and morbidity. Early detecti...

Multi-level Regulatory Roles of Lactate Metabolism Gene Network in Oral Cancer: Machine Learning Insights

This study explores the multi-level regulatory roles of the lactate metabolism gene network in oral ...

Development of a Risk Prediction Model for Sepsis-Related Delirium Based on Multiple Machine Learning Approaches and an Online Calculator

Sepsis-associated delirium (SAD) occurs due to disruptions in neurotransmission linked to inflammato...

Machine Learning Improves the Predictive Utility of Lactic Acid in Hospitalized Infants

Hyperlactatemia is common in hospitalized infants. Machine learning was applied to clinical and labo...

Integrating a host transcriptomic biomarker with a large language model for diagnosis of lower respiratory tract infection

Lower respiratory tract infections (LRTIs) are a leading cause of mortality worldwide and can be dif...

Machine learning identifies clinical sepsis phenotypes that translate to the plasma proteome: a prospective cohort study

Sepsis therapy is still limited to treatment of the underlying infection and supportive measures. To...

Predicting Bacterial Vaginosis Development using Artificial Neural Networks

Bacterial vaginosis (BV) is a dysbiosis of the vaginal microbiome, characterized by the depletion of...

Machine Learning-based Mortality Prediction for Pediatric Fulminant Myocarditis Using Cytokine Profiles

Fulminant myocarditis (FM) is a rare but life-threatening pediatric condition that rapidly progresse...

Plasma proteomics identifies molecular subtypes in sepsis

The heterogeneity of sepsis represents a significant challenge to the development of personalized se...

STM-GNN: Space-Time-and-Memory Graph Neural Networks for Predicting Multi-Drug Resistance Risks in Dynamic Patient Networks

Hospital-acquired infections (HAIs), particularly those caused by multidrug-resistant (MDR) bacteria...

Leveraging Machine Learning and Clinical Data to Predict Response to Intralesional Corticosteroids in Keloid Patients

Intralesional corticosteroid injections (ILCS) are a common treatment for keloid lesions; however, m...

Dense sampling of choices links high learning rates to obesity and low reward sensitivity to binge eating

Mounting evidence shows that obesity is associated with alterations in dopamine transmission. Howeve...

Outbreak and Postnatal Antibiotic Exposures Drive the Development Trajectory of the Nasopharyngeal Microbiota in the First Year of Life

Early exposure to antibiotics and prolonged hospitalization in preterm infants may perturb microbiom...

AI Implementation in U.S. Healthcare and Its Association With Elder Mortality and Quality of Care

Hospitals are increasingly adopting artificial intelligence (AI) tools in clinical care. However, th...

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COVID-19 modulates pregnancy outcomes

The COVID-19 pandemic exposed many pregnant individuals to SARS-CoV-2. Literature suggests a link be...

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