Critical Care

Sepsis

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

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Critical-Care Subcategories: Sepsis
Showing 442-462 of 9,027 articles
A new scoring in differential diagnosis: multisystem inflammatory syndrome or adenovirus infection?

BACKGROUND/AIM: Differentiating multisystem inflammatory syndrome in children (MIS-C) from adenoviru...

AmpClass: an Antimicrobial Peptide Predictor Based on Supervised Machine Learning.

In the last decades, antibiotic resistance has been considered a severe problem worldwide. Antimicro...

Is artificial intelligence prepared for the 24-h shifts in the ICU?

Integrating machine learning (ML) into intensive care units (ICUs) can significantly enhance patient...

Development and validation of a sepsis risk index supporting early identification of ICU-acquired sepsis: an observational study.

BACKGROUND: Sepsis is a threat to global health, and domestically is the major cause of in-hospital ...

AI-Driven Realtime Monitoring of Early Indicators for Ichthyophthirius multifiliis Infection of Rainbow Trout.

A novel video-based real-time system based on AI (artificial intelligence) was developed to detect c...

Transfer learning-enabled outcome prediction for guiding CRRT treatment of the pediatric patients with sepsis.

Continuous renal replacement therapy (CRRT) is a life-saving procedure for sepsis but the benefit of...

Machine-learning-based evaluation of the usefulness of lactate for predicting neonatal mortality in preterm infants.

BACKGROUND: Unlike in adult and pediatric patients, the usefulness of lactate in preterm infants has...

Bowel preparation before elective right colectomy: Multitreatment machine-learning analysis on 2,617 patients.

BACKGROUND: In the worldwide, real-life setting, some candidates for right colectomy still receive n...

High Spatiotemporal Precision Mapping of Optical Nanosensor Array Using Machine Learning.

Optical nanosensors, including single-walled carbon nanotubes (SWCNTs), provide real-time spatiotemp...

A machine learning-based electronic nose for detecting neonatal sepsis: Analysis of volatile organic compound biomarkers in fecal samples.

BACKGROUND: Neonatal sepsis is a global health threat, contributing to high morbidity and mortality ...

A Machine Learning Algorithm Suggests Repurposing Opportunities for Targeting Selected GPCRs.

Repurposing utilizes existing drugs with known safety profiles and discovers new uses by combining e...

Metabolomic profiling of dengue infection: unraveling molecular signatures by LC-MS/MS and machine learning models.

BACKGROUND & OBJECTIVE: The progression of dengue fever to severe dengue (SD) is a major public heal...

Predictive modeling of hepatitis B viral dynamics: a caputo derivative-based approach using artificial neural networks.

A fractional model for the kinetics of hepatitis B transmission was developed. The hepatitis B virus...

Deep humoral profiling coupled to interpretable machine learning unveils diagnostic markers and pathophysiology of schistosomiasis.

Schistosomiasis, a highly prevalent parasitic disease, affects more than 200 million people worldwid...

Virus-host interactions predictor (VHIP): Machine learning approach to resolve microbial virus-host interaction networks.

Viruses of microbes are ubiquitous biological entities that reprogram their hosts' metabolisms durin...

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