Critical Care

Sepsis

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

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Critical-Care Subcategories: Sepsis
Showing 526-546 of 9,008 articles
Machine learning for the prediction of 1-year mortality in patients with sepsis-associated acute kidney injury.

INTRODUCTION: Sepsis-associated acute kidney injury (SA-AKI) is strongly associated with poor progno...

A decision support system for the detection of cutaneous fungal infections using artificial intelligence.

Cutaneous fungal infections are one of the most common skin conditions, hence, the burden of determi...

Classification and regression machine learning models for predicting the combined toxicity and interactions of antibiotics and fungicides mixtures.

Antibiotics and triazole fungicides coexist in varying concentrations in natural aquatic environment...

Predicting Clostridioides difficile infection outcomes with explainable machine learning.

BACKGROUND: Clostridioides difficile infection results in life-threatening short-term outcomes and t...

Robot-related injuries in the workplace: An analysis of OSHA Severe Injury Reports.

Industrial robots are increasingly commonplace, but research on prototypical accidents and injuries ...

Predicting Survival in Patients with Advanced NSCLC Treated with Atezolizumab Using Pre- and on-Treatment Prognostic Biomarkers.

Existing survival prediction models rely only on baseline or tumor kinetics data and lack machine le...

Metabolism score and machine learning models for the prediction of esophageal squamous cell carcinoma progression.

The incomplete prediction of prognosis in esophageal squamous cell carcinoma (ESCC) patients is attr...

A rapid approach with machine learning for quantifying the relative burden of antimicrobial resistance in natural aquatic environments.

The massive use and discharge of antibiotics have led to increasing concerns about antimicrobial res...

Early diagnosis of HIV cases by means of text mining and machine learning models on clinical notes.

Undiagnosed and untreated human immunodeficiency virus (HIV) infection increases morbidity in the HI...

Factors of acute respiratory infection among under-five children across sub-Saharan African countries using machine learning approaches.

Symptoms of Acute Respiratory infections (ARIs) among under-five children are a global health challe...

Machine Learning Prediction of Small Molecule Accumulation in Enhanced with Descriptor Statistics.

Antibiotic resistance, particularly among Gram-negative bacteria, poses a significant healthcare cha...

Machine learning models to predict systemic inflammatory response syndrome after percutaneous nephrolithotomy.

OBJECTIVE: The objective of this study was to develop and evaluate the performance of machine learni...

Ensemble Machine Learning and Predicted Properties Promote Antimicrobial Peptide Identification.

The emergence of antibiotic-resistant microbes raises a pressing demand for novel alternative treatm...

Artificial intelligence in Parkinson's disease: Early detection and diagnostic advancements.

Parkinson's disease (PD) is the second most common neurodegenerative disorder, globally affecting me...

Development and external validation of machine learning-based models to predict patients with cellulitis developing sepsis during hospitalisation.

OBJECTIVE: Cellulitis is the most common cause of skin-related hospitalisations, and the mortality o...

Risk assessment and prediction of nosocomial infections based on surveillance data using machine learning methods.

BACKGROUND: Nosocomial infections with heavy disease burden are becoming a major threat to the healt...

Discovery of urinary biosignatures for tuberculosis and nontuberculous mycobacteria classification using metabolomics and machine learning.

Nontuberculous mycobacteria (NTM) infection diagnosis remains a challenge due to its overlapping cli...

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