Critical Care

Sepsis

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

9,027 articles
Stay Ahead - Weekly Sepsis research updates
Subscribe
Browse Specialties
Critical-Care Subcategories: Sepsis
Showing 379-399 of 9,027 articles
Predicting intra-abdominal candidiasis in elderly septic patients using machine learning based on lymphocyte subtyping: a prospective cohort study.

OBJECTIVE: Intra-abdominal candidiasis (IAC) is difficult to predict in elderly septic patients with...

Systematic evaluation of machine learning models for postoperative surgical site infection prediction.

BACKGROUND: Surgical site infections (SSIs) lead to increased mortality and morbidity, as well as in...

Antibiotic SERS spectral analysis based on data augmentation and attention mechanism strategy.

The analysis of Raman spectrum data has gradually transitioned into the era of machine learning. How...

Possible biocontrol of bacterial blight in pomegranate using native endophytic spp. under field conditions.

Bacterial blight in pomegranate, caused by pv. (Xcp), is one of the most devastating diseases, lea...

Machine learning algorithms for the early detection of bloodstream infection in children with osteoarticular infections.

BACKGROUND: Bloodstream infection (BSI) poses a significant life-threatening risk in pediatric patie...

Rapid diagnosis of bacterial vaginosis using machine-learning-assisted surface-enhanced Raman spectroscopy of human vaginal fluids.

UNLABELLED: Bacterial vaginosis (BV) is an abnormal gynecological condition caused by the overgrowth...

Impact of Inflammation After Cardiac Surgery on 30-Day Mortality and Machine Learning Risk Prediction.

OBJECTIVES: To investigate the impact of systemic inflammatory response syndrome (SIRS) on 30-day mo...

Potato Late Blight Outbreak: A Study on Advanced Classification Models Based on Meteorological Data.

While past research has emphasized the importance of late blight infection detection and classificat...

Machine learning-enhanced assessment of potential probiotics from healthy calves for the treatment of neonatal calf diarrhea.

Neonatal calf diarrhea (NCD) remains a significant contributor to calf mortality within the first 3 ...

A novel approach to antimicrobial resistance: Machine learning predictions for carbapenem-resistant Klebsiella in intensive care units.

This study was conducted at Kocaeli University Hospital in Turkey and aimed to predict carbapenem-re...

Prediction of mortality in sepsis patients using stacked ensemble machine learning algorithm.

INTRODUCTION: Machine learning (ML) has been tried in predicting outcomes following sepsis. This stu...

Heparin in sepsis: current clinical findings and possible mechanisms.

Sepsis is a clinical syndrome resulting from the interaction between coagulation, inflammation, immu...

Machine learning-based prediction of antibiotic resistance in Mycobacterium tuberculosis clinical isolates from Uganda.

BACKGROUND: Efforts toward tuberculosis management and control are challenged by the emergence of My...

A machine-learning model for prediction of Acinetobacter baumannii hospital acquired infection.

BACKGROUND: Acinetobacter baumanni infection is a leading cause of morbidity and mortality in the In...

Using machine learning for personalized prediction of longitudinal coronavirus disease 2019 vaccine responses in transplant recipients.

The coronavirus disease 2019 pandemic has underscored the importance of vaccines, especially for imm...

Artificial intelligence-driven quantification of antibiotic-resistant Bacteria in food by color-encoded multiplex hydrogel digital LAMP.

Antibiotic-resistant bacteria pose considerable risks to global health, particularly through transmi...

PREDICTING IN-HOSPITAL MORTALITY IN CRITICAL ORTHOPEDIC TRAUMA PATIENTS WITH SEPSIS USING MACHINE LEARNING MODELS.

Purpose: This study aims to establish and validate machine learning-based models to predict death in...

Machine Learning-based Prediction of Blood Stream Infection in Pediatric Febrile Neutropenia.

OBJECTIVES: This study aimed to develop machine learning (ML) prediction models for identifying bloo...

Browse Specialties