Sepsis

Diagnosing melioidosis and tracking treatment outcomes using breath.

Melioidosis is a life-threatening infectious disease caused by Burkholderia pseudomallei (Bp). Rapid...

Nano-antimicrobial peptides (Nano-AMPs) to combat resistant gram-negative bacteria.

The emergence of antimicrobial resistance (AMR) poses a critical threat to public health worldwide, ...

Predicting early discontinuation of adalimumab in patients with rheumatoid arthritis using machine learning: A specialty pharmacy-based approach.

BACKGROUND: Patients with rheumatoid arthritis (RA) prescribed adalimumab often discontinue treatmen...

Evaluating Guideline-Adherent Antibiotic Use for Skin Infections Using Natural Language Processing: A Pilot Study.

OBJECTIVE: To develop and evaluate an internally validated natural language processing (NLP) model t...

Biomimetic Electrochemical Chip Integrated with Closed-Loop AI for Dynamic Dopamine Decoding and Neuromodulation.

Bioelectronic systems integrated with artificial intelligence (AI) are transforming neurochemical di...

AI-enhanced therapeutic drug monitoring for vancomycin and β-lactam antibiotics in critical care: from population PK to bedside algorithms.

INTRODUCTION: Although sepsis and other severe infections in intensive care are common and deadly, o...

Fcer1g and St3gal1: Macrophage-associated angiogenesis biomarkers and therapeutic targets in sepsis-induced acute lung injury.

BACKGROUND: Acute lung injury (ALI) involves the release of growth factors and inflammatory mediator...

Acute respiratory infection (COVID-19) risk prediction in travelers: A random forest model.

BACKGROUND: Early screening during outbreaks of acute respiratory infections (ARIs) is critical for ...

Early hemodynamic phenotyping in sepsis using transthoracic echocardiography: A proof-of-concept study in a north African ICU.

BACKGROUND: Cardiovascular dysfunction in sepsis is heterogeneous and contributes to poor outcomes. ...

Machine learning analysis of s-EASIX for predicting 30-day mortality in sepsis patients from MIMIC-IV.

Endothelial dysfunction is an important risk factor for the progression of sepsis. The simplified en...

Construction of interpretable machine-learning diagnostic models for erectile dysfunction based on routine blood and biochemical detection data.

Despite its high incidence, the diagnosis of erectile dysfunction (ED) is impeded by current diagnos...

Development and validation of a predictive model for profiling antibiotic resistance phenotypes of Acinetobacter baumannii strains via clinical MALDI-TOF mass spectra: A multicenter study.

Acinetobacter baumannii is a significant pathogen responsible for healthcare-acquired infections (HA...

Operationalizing Sepsis Definitions With Artificial Intelligence: Toward Smarter Antibiotic Use.

Discovery of H2 Receptor Antagonists as Colistin Enhancers by Targeting Acid Stress Response.

Plasmid-mediated colistin resistance gene mcr has markedly diminished the effectiveness of colistin ...

A machine learning model for prediction of early-onset neonatal sepsis in low-income and middle-income countries: development and validation study.

OBJECTIVE: Early-onset sepsis (EOS), which occurs within the first 72 hours of life, can often be fa...

Nomogram based on the pre-treatment systemic oxidative stress score to predict the prognosis of surgically treated patients with oral squamous cell carcinoma: competing risk model analysis.

The aim of this study was to explore the prognostic predictive importance of the pre-treatment syste...

Explainable multimodal deep learning models for variable-length sequences in critically ill patients.

OBJECTIVE: Deep learning models have shown strong performance in predicting clinical events in criti...

A Surface-Enhanced Raman Scattering-Digital Microfluidics Biosensing Platform Integrated with a 1D-Convolutional Neural Network for Noninvasive Detection of Inflammation Markers.

The noninvasive detection of multiple inflammatory markers (IMs) for early sepsis diagnosis is chall...

Integration of single-cell and bulk transcriptomics with machine learning identifies LDHA as a lactate-related diagnostic and prognostic biomarker in sepsis.

Improved outcomes and donor utilization in heart transplantation with 10 °C static cold storage.

OBJECTIVE: To compare 10 °C static cold storage (SCS) with traditional ice for cardiac allograft pre...

Toxoplasma gondii infection in wildlife in China (1985-2024): A systematic review and meta-analysis with machine learning.

The globally distributed zoonotic protozoan parasite Toxoplasma gondii presents escalating conservat...