Critical Care

Sepsis

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

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Critical-Care Subcategories: Sepsis
Showing 358-378 of 9,027 articles
Predictive modelling of hospital-acquired infection in acute ischemic stroke using machine learning.

Hospital-acquired infections (HAIs) are serious complication for patients with acute ischemic stroke...

Hope for the best prepare for the worst: acute kidney disease and catastrophic comorbidities (a case report).

It is evident that Acute Kidney Injury (AKI) is an independent risk factor for both the survival of ...

The predictive value of heparin-binding protein for bacterial infections in patients with severe polytrauma.

INTRODUCTION: Heparin-binding protein is an inflammatory factor with predictive value for sepsis and...

Machine learning for predicting acute myocardial infarction in patients with sepsis.

Acute myocardial infarction (AMI) and sepsis are the leading causes of high mortality rates in inten...

Pulmonologists-level lung cancer detection based on standard blood test results and smoking status using an explainable machine learning approach.

Lung cancer (LC) remains the primary cause of cancer-related mortality, largely due to late-stage di...

Predicting the infecting dengue serotype from antibody titre data using machine learning.

The development of a safe and efficacious vaccine that provides immunity against all four dengue vir...

External validation of predictive models for antibiotic susceptibility of urine culture.

OBJECTIVE: To develop, externally validate, and test a series of computer algorithms to accurately p...

Empirical Comparison and Analysis of Artificial Intelligence-Based Methods for Identifying Phosphorylation Sites of SARS-CoV-2 Infection.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a member of the large coronavirus fa...

Machine learning for the prediction of mortality in patients with sepsis-associated acute kidney injury: a systematic review and meta-analysis.

BACKGROUND: Predicting mortality in sepsis-related acute kidney injury facilitates early data-driven...

Comparative transcriptomic and molecular biology analyses to explore potential immune responses to challenge in .

is a significant pathogen affecting shrimp and crab farming, particularly strains carrying genes as...

Antimicrobial Activity of Tea and Agarwood Leaf Extracts Against Multidrug-Resistant Microbes.

Emerging multidrug-resistant (MDR) strains are the main challenges to the progression of new drug di...

Recognizing SARS-CoV-2 infection of nasopharyngeal tissue at the single-cell level by machine learning method.

SARS-CoV-2 has posed serious global health challenges not only because of the high degree of virus t...

Rapid Deployment of Antiviral Drugs Using Single-Virus Tracking and Machine Learning.

The outbreak of emerging acute viral diseases urgently requires the acceleration of specialized anti...

Analysis of HIV infection among voluntary blood donors based on HIV ELISA and nucleic acid detection.

OBJECTIVE: To analyze the epidemiological characteristics of human immunodeficiency virus (HIV) infe...

Antibacterial Activity of Crude , , and Methanolic Extracts on serovar Manilae.

BACKGROUND AND OBJECTIVE: Leptospirosis is a disease caused by pathogenic prevalent in tropical cou...

extract in combination with lytic phage cocktails: a promising therapeutic approach against biofilms of multi-drug resistant .

Antimicrobial resistance (AMR) poses a significant global threat to public health systems, rendering...

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