Critical Care

Sepsis

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

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Critical-Care Subcategories: Sepsis
Showing 631-651 of 9,021 articles
Parkinson's disease diagnosis using deep learning: A bibliometric analysis and literature review.

Parkinson's Disease (PD) is a progressive neurodegenerative illness triggered by decreased dopamine ...

Machine Learning-Assistant Colorimetric Sensor Arrays for Intelligent and Rapid Diagnosis of Urinary Tract Infection.

Urinary tract infections (UTIs), which can lead to pyelonephritis, urosepsis, and even death, are am...

Going to extremes: progress in exploring new environments for novel antibiotics.

The discoveries of penicillin and streptomycin were pivotal for infection control with the knowledge...

sAMP-VGG16: Force-field assisted image-based deep neural network prediction model for short antimicrobial peptides.

During the last three decades, antimicrobial peptides (AMPs) have emerged as a promising therapeutic...

Machine Learning Analysis Using RNA Sequencing to Distinguish Neuromyelitis Optica from Multiple Sclerosis and Identify Therapeutic Candidates.

This study aims to identify RNA biomarkers distinguishing neuromyelitis optica (NMO) from relapsing-...

Biodegradation of ciprofloxacin using machine learning tools: Kinetics and modelling.

Recently, the rampant administration of antibiotics and their synthetic organic constitutes have exa...

Development and Validation of an Interpretable Conformal Predictor to Predict Sepsis Mortality Risk: Retrospective Cohort Study.

BACKGROUND: Early and reliable identification of patients with sepsis who are at high risk of mortal...

Understanding COVID-19 infection among people with intellectual and developmental disabilities using machine learning.

BACKGROUND: People with intellectual and developmental disabilities (IDD) were disproportionately af...

Assisting the infection preventionist: Use of artificial intelligence for health care-associated infection surveillance.

BACKGROUND: Health care-associated infection (HAI) surveillance is vital for safety in health care s...

Presynaptic Dopaminergic Imaging Characterizes Patients with REM Sleep Behavior Disorder Due to Synucleinopathy.

OBJECTIVE: To apply a machine learning analysis to clinical and presynaptic dopaminergic imaging dat...

Prognosis of COVID-19 severity using DERGA, a novel machine learning algorithm.

It is important to determine the risk for admission to the intensive care unit (ICU) in patients wit...

Deep model predictive control of gene expression in thousands of single cells.

Gene expression is inherently dynamic, due to complex regulation and stochastic biochemical events. ...

Construction of an aerolysin-based multi-epitope vaccine against an machine learning and artificial intelligence-supported approach.

, a gram-negative coccobacillus bacterium, can cause various infections in humans, including septic ...

Antibiotic combinations prediction based on machine learning to multicentre clinical data and drug interaction correlation.

BACKGROUND: With increasing antibiotic resistance and regulation, the issue of antibiotic combinatio...

EnAMP: A novel deep learning ensemble antibacterial peptide recognition algorithm based on multi-features.

Antimicrobial peptides (AMPs), as the preferred alternatives to antibiotics, have wide application w...

Predicting S. aureus antimicrobial resistance with interpretable genomic space maps.

Increasing antimicrobial resistance (AMR) represents a global healthcare threat. To decrease the spr...

Raman spectrum combined with deep learning for precise recognition of Carbapenem-resistant Enterobacteriaceae.

Carbapenem-resistant Enterobacteriaceae (CRE) is a major pathogen that poses a serious threat to hum...

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