Sepsis

Prediction of sepsis among patients with major trauma using artificial intelligence: a multicenter validated cohort study.

BACKGROUND: Sepsis remains a significant challenge in patients with major trauma in the ICU. Early detection and treatment are crucial for improving outcomes and reducing mortality rates. Nonetheless, clinical tools for predicting sepsis among patients with major trauma are limited. This study aimed to develop and validate an artificial intelligence (AI) platform for predicting the risk of sepsis ...

Quantification of L-lactic acid in human plasma samples using Ni-based electrodes and machine learning approach.

This work presents a robust strategy for quantifying overlapping electrochemical signatures originating from complex mixtures and real human plasma samples using nickel-based electrochemical sensors and machine learning (ML). This strategy enables the detection of a panel of analytes without being limited by the selectivity of the transducer material and leaving accommodation of interference analy...

Deep learning on CT scans to predict checkpoint inhibitor treatment outcomes in advanced melanoma.

Immune checkpoint inhibitor (ICI) treatment has proven successful for advanced melanoma, but is associated with potentially severe toxicity and high c...

Identification of sepsis-associated encephalopathy biomarkers through machine learning and bioinformatics approaches.

Sepsis-associated encephalopathy (SAE) is common in septic patients, characterized by acute and long-term cognitive impairment, and is associated with...

Using genomic data and machine learning to predict antibiotic resistance: A tutorial paper.

Antibiotic resistance is a global public health concern. Bacteria have evolved resistance to most antibiotics, which means that for any given bacteria...

Allogenic faecal microbiota transplantation for antibiotic-associated diarrhoea in critically ill patients (FEBATRICE)-Study protocol for a multi-centre randomised controlled trial (phase II).

BACKGROUND: Exposure of critically ill patients to antibiotics lead to intestinal dysbiosis, which often manifests as antibiotic-associated diarrhoea....

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 patients and their kidneys. Here, we present a cas...

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 participates in the inflammatory response through...

Evaluating Neural Network Performance in Predicting Disease Status and Tissue Source of JC Polyomavirus from Patient Isolates Based on the Hypervariable Region of the Viral Genome.

JC polyomavirus (JCPyV) establishes a persistent, asymptomatic kidney infection in most of the population. However, JCPyV can reactivate in immunocomp...

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 diagnoses. Effective strategies for early detection ...

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 intensive care units. While sepsis frequently affects t...

Phytochemical Composition, Antibacterial, and Antibiotic-Resistance Modulatory Activity of Extracts of Moldenke M. A. Lawson, and L. Against Multidrug-Resistant .

is a critical-class pathogen that shows great resistance to most conventional antibiotics. Hence, it is of utmost importance to search for novel drug...

Machine learning approach and geospatial analysis to determine HIV infection, awareness status, and transmission knowledge among adults in Sub-Saharan Africa.

BACKGROUND: HIV/AIDS remains a major public health challenge, in Sub-Saharan Africa (SSA). In 2020, 16% of people living with HIV did not know their H...

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 virus serotypes is a priority, and a significant chal...

Identification and experimental validation of diagnostic and prognostic genes CX3CR1, PID1 and PTGDS in sepsis and ARDS using bulk and single-cell transcriptomic analysis and machine learning.

BACKGROUND: Sepsis is an uncontrolled reaction to infection that causes severe organ dysfunction and is a primary cause of ARDS. Patients suffering bo...

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 predict antibiotic susceptibility test (AST) result...

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 treatment decisions. Machine learning is predicti...

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 associated with acute hepatopancreatic necrosis synd...

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 discovery. To diminish infectious disease-causing pa...

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 transmissibility but also due to its severe effects...