Critical Care

Sepsis

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

7,154 articles
Stay Ahead - Weekly Sepsis research updates
Subscribe
Browse Categories
Critical-Care Subcategories: Sepsis
Showing 2857-2877 of 7,154 articles
Machine Learning-Based Identification of Sickle Cell Disease Subphenotypes in Clinical Trial Data

Sickle Cell Disease (SCD) is a rare autosomal recessive disorder caused by a point mutation producin...

Urinary collagen peptides predict mortality

Organ fibrosis caused by the presence of excessive extracellular matrix (ECM) is strongly related to...

Nucleotide motif-guided selection of plasma microRNA biomarkers for organ injury prediction in trauma

Trauma remains a leading cause of morbidity and mortality in part due to secondary organ injury and ...

Evaluation of a real time machine learning sepsis risk algorithm for Emergency Department waiting rooms (SAFE-WAIT)

To evaluate and compare the real-time Sepsis risk Artificial intelligence algorithm For Emergency de...

Prediction of impulse control disorders in Parkinson’s disease: a longitudinal machine learning study

Impulse control disorders (ICD) in Parkinson’s disease (PD) patients mainly occur as adverse effects...

CLIF-Net: Intersection-guided Cross-view Fusion Network for Infection Detection from Cranial Ultrasound

This paper addresses the problem of detecting possible serious bacterial infection (pSBI) of infancy...

Case-Control Matching Erodes Feature Discriminability for AI-driven Sepsis Prediction in ICUs: A Retrospective Cohort Study

Sepsis remains a leading cause of intensive care unit (ICU) mortality worldwide, and early detection...

Development of a pilot machine learning model to predict successful cure in critically ill patients with community-acquired pneumonia

Severe community-acquired pneumonia (CAP) remains a major cause of critical illness, yet there are n...

Incidence of Long COVID Following Reinfection with COVID-19

COVID-19 reinfections have emerged as a critical concern, particularly in relation to post-acute seq...

Development and Validation of VC-MAES and VC-SEPS: Deep Learning-Based Early Warning Systems for Hospitalized Patients

The timely detection of ward deterioration—including unplanned intensive care unit (ICU) transfer, c...

Predicting Tuberculosis Incidence in Adult HIV Patients on ART in Debre Markos, Ethiopia: A Machine Learning Approach

Tuberculosis (TB) is the commonest comorbidity among individuals with HIV/AIDS, especially in low- a...

Human breast cancer is linked to Epstein-Barr virus because it targets stem cells: bioinformatic chromosome correlations

Breast cancer originates from rare “cancer stem cells”. Stem cells are especially susceptible to bec...

Evaluating Deep Learning Sepsis Prediction Models in ICUs Under Distribution Shift: A Multi-Centre Retrospective Cohort Study

Sepsis remains a leading cause of mortality in intensive care units (ICUs) worldwide, underscoring t...

Individualized treatment effects of corticosteroids in IgA nephropathy

IgA nephropathy (IgAN) is a leading cause of kidney failure with diverse clinical presentations and ...

Personalized Hemodynamic Management Using Reinforcement Learning to Prevent Persistent Acute Kidney Injury After Cardiac Surgery

Acute kidney injury (AKI) affects one-third of patients after cardiac surgery and increases morbidit...

Browse Categories