Sepsis

A Knowledge Graph for the Exploration of Human RSV Infection.

Despite decades of research and disease burden, RSV remains the most common cause of acute lower respiratory tract infection (ALRTI) in infants <2 years of age. New vaccines and an improved long lasting monoclonal antibody have been approved to protect individuals at increased risk of severe disease. However, treatment of severe RSV-mediated disease remains palliative, and we still cannot identify...

SERS-ATB: A comprehensive database server for antibiotic SERS spectral visualization and deep-learning identification.

The rapid and accurate identification of antibiotics in environmental samples is critical for addressing the growing concern of antibiotic pollution, particularly in water sources. Antibiotic contamination poses a significant risk to ecosystems and human health by contributing to the spread of antibiotic resistance. Surface-enhanced Raman spectroscopy (SERS), known for its high sensitivity and spe...

SERS based determination of ceftriaxone, ampicillin, and vancomycin in serum using WS/Au@Ag nanocomposites and a 2D-CNN regression model.

Accurate therapeutic drug monitoring (TDM) of antibiotics including ceftriaxone, ampicillin, and vancomycin plays an important role in the treatment o...

Contextual Phenotyping of Pediatric Sepsis Cohort Using Large Language Models

Clustering patient subgroups is essential for personalized care and efficient resource use. Traditional clustering methods struggle with high-dimens...

The gut microbiome and metabolome in children with a first febrile urinary tract infection: a pilot study.

BACKGROUND: Urinary tract infection (UTI) is a common bacterial infection in the pediatric population. Febrile urinary tract infection (fUTI) can lead...

Tutorial: guidelines for the use of machine learning methods to mine genomes and proteomes for antibiotic discovery.

Genomes and proteomes constitute a rich reservoir of molecular diversity. However, they have remained underexplored because of a lack of appropriate t...

In-depth analysis of the risk factors for persistent severe acute respiratory syndrome coronavirus 2 infection and construction of predictive models: an exploratory research study.

BACKGROUND: Persistent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection differs from long coronavirus disease (COVID-19) (acute ...

Predicting sepsis treatment decisions in the paediatric emergency department using machine learning: the AiSEPTRON study.

BACKGROUND: Early identification of children at risk of sepsis in emergency departments (EDs) is crucial for timely treatment and improved outcomes. E...

Development and application of an early prediction model for risk of bloodstream infection based on real-world study.

BACKGROUND: Bloodstream Infection (BSI) is a severe systemic infectious disease that can lead to sepsis and Multiple Organ Dysfunction Syndrome (MODS)...

Predictors and associations of complications in ureteroscopy for stone disease using AI: outcomes from the FLEXOR registry.

We aimed to develop machine learning(ML) algorithms to evaluate complications of flexible ureteroscopy and laser lithotripsy(fURSL), providing a valid...

SEMTWIST Quantification of Biofilm Infection in Human Chronic Wound Using Scanning Electron Microscopy and Machine Learning.

To develop scanning electron microscopy-based Trainable Weka (Waikato Environment for Knowledge Analysis) Intelligent Segmentation Technology (SEMTWI...

Severe community-acquired pneumonia (sCAP): advances in management and future directions.

Severe community-acquired pneumonia (sCAP) is a major global health challenge, with high morbidity and mortality, especially among patients requiring ...

Multicenter target trial emulation to evaluate corticosteroids for sepsis stratified by predicted organ dysfunction trajectory.

Corticosteroids decrease the duration of organ dysfunction in sepsis and a range of overlapping and complementary infectious critical illnesses, inclu...

The Effect of Early Warning Systems for Sepsis on Mortality: A Systematic Review and Meta-analysis.

BACKGROUND: The Surviving Sepsis Campaign strongly recommends that all hospitals screen for sepsis as part of performance improvement. The effect of s...

Personalized Nutrition Strategies for Patients in the Intensive Care Unit: A Narrative Review on the Future of Critical Care Nutrition.

Critically ill patients in intensive care units (ICUs) are at high risk of malnutrition, which can result in muscle atrophy, polyneuropathy, increase...

The contribution of the locus coeruleus - norepinephrine system to the coupling between pupil-linked arousal and cortical state.

Understanding how pupil-linked arousal couples with cortical state is crucial for uncovering the neural mechanisms underlying brain state-dependent co...

Analyzing Key Predictors of Postoperative Delirium Following Coronary Artery Bypass Grafting and Aortic Valve Replacement: A Machine Learning Perspective.

: Postoperative delirium (POD) is a frequent and severe complication following cardiac surgery, particularly in high-risk patients undergoing coronary...

Identifying Mild-to-Moderate Atopic Dermatitis Using a Generic Machine Learning Approach: A Danish National Health Register Study.

Atopic dermatitis is a chronic skin disease, causing itching and recurrent eczematous lesions. In Danish national register data, adults with atopic de...

A novel sensor array combined with machine learning for the effective differentiation of multiple classes of antibiotics based on copper-based nanozymes with laccase-like activity.

A nanozyme sensor array was developed combining with machine learning algorithms for the effective identification and differentiation of multiple anti...

A deep learning and molecular modeling approach to repurposing Cangrelor as a potential inhibitor of Nipah virus.

Deforestation, urbanization, and climate change have significantly increased the risk of zoonotic diseases. Nipah virus (NiV) of Paramyxoviridae famil...