Sepsis

Global Adoption and Readiness for Artificial Intelligence (AI) and Digital Health Technologies in Infection Prevention and Control (IPC): A WHO Global Survey.

BACKGROUND: Artificial intelligence and digital health technologies may strengthen Infection Prevention and Control through enhanced surveillance, decision-making, and workforce training. However, global evidence on their uptake and perceived usefulness among IPC professionals remains limited. METHODS: This cross-sectional online survey coordinated by the World Health Organization between 21 March...

Efficiently quantifying thermodynamic and kinetic effects of biochar pyrolysis parameters on antibiotic adsorption from water using interpretable causal machine learning.

Antibiotic pollution in aquatic environments threatens ecological and public health. Biochar is a promising biomass-derived adsorbent, yet its performance is profoundly influenced by pyrolysis parameters. This study aimed to develop an interpretable causal machine learning (ICML) framework to quantify the net causal effects of pyrolysis parameters, thereby providing targeted guidance for biochar p...

MRI-based radiomics explainable model for predicting recurrence of limb chronic osteomyelitis in limb bones treated by Masquelet technique.

AIMS: This study aimed to develop a machine learning model for predicting chronic osteomyelitis recurrence (COR) following the Masquelet technique (MT...

An Intelligent Photocatalytic Self-Cleaning SERS Platform with Machine Learning for On-Site Detection of Multiple Antibiotics.

The widespread use of antibiotics in aquaculture has led to persistent residues in aquatic environments, necessitating the development of sensitive, s...

Glycolytic reprogramming in host response to Borrelia burgdorferi: A gene signature revealed by integrative bioinformatics analysis and machine learning.

Lyme disease (LD), a multifaceted condition caused by Borrelia burgdorferi (Bb), remains poorly understood, particularly regarding metabolic pathways....

Machine learning-driven decision support for antibiotic optimization in typhoid fever based on patient profiles.

INTRODUCTION: Typhoid fever remains a major Global public health concern, with treatment outcomes strongly influenced by antimicrobial resistance (AMR...

Interpretable machine learning for predicting in-hospital mortality in COPD ICU patients: a rigorous validation across time and geography.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a common reason for admission to the intensive care unit (ICU), where accurate risk strati...

ARDSMLpred: A machine learning model for predicting SCAP-associated ARDS based on MIMIC-IV database.

BACKGROUND: Early identification of acute respiratory distress syndrome (ARDS) in severe community-acquired pneumonia (SCAP) are crucial for reducing ...

WormSpot: a machine learning-powered viability scoring platform in C. elegans for Candida pathogenicity studies.

UNLABELLED: Invasive Candida infections pose a critical health challenge, exacerbated by emerging antifungal resistance. Caenorhabditis elegans (C. el...

A geometry-aware generative framework integrating GPS-VAE and Transformer-SELFIES for structure-based de novo drug design.

CONTEXT: Designing novel ligands tailored to specific protein binding pockets remains a core objective in structure-based de novo drug design (SBDD). ...

SPECT hybrid approach combining conventional and deep features for early detection of Parkinson's disease.

The early diagnosis of Parkinson's disease (PD) using SPECT imaging continues to be challenging due to the subtle dopaminergic deficits present in the...

Dissecting the pathobiology of suspected sepsis through a comparative analysis of endothelial inflammatory and clinical prediction models.

Sepsis remains a formidable challenge in critical care, and is characterized by profound circulatory and cellular abnormalities driven by both systemi...

Integrated Prediction of Ceftriaxone Resistance in Major Salmonella Serotypes Using MALDI-TOF MS Data with Balanced Datasets and Machine Learning.

OBJECTIVES: Salmonella causes gastroenteritis and invasive infections worldwide, and rising ceftriaxone resistance complicates empirical therapy. Conv...

Exploring the Bone-Vascular Axis: AI-Augmented Chest CT Analysis in COPD Highlights Association Between Vertebral Bone Density and Arterial Calcifications.

OBJECTIVES: Artificial intelligence (AI) tools enable automated assessment of vertebral bone mineral density (BMD), coronary artery calcification (CAC...

Diagnostic accuracy of serum and synovial biomarker thresholds for diagnosing periprosthetic joint infection: a QUADAS-C-guided systematic review and meta-analysis.

BACKGROUND: Periprosthetic joint infection (PJI) remains one of the most serious complications after joint arthroplasty, and accurate diagnosis contin...

Screening of Sepsis Diagnostic Biomarkers Based on Fumarate Metabolism-Related Genes with Analysis of Immune Infiltration and Subtype Identification.

BACKGROUND: Sepsis is a major global health challenge characterized by a complex pathogenesis involving an early hyperinflammatory phase followed by a...

GATA3 mediates the cardioprotective effect of hydroxysafflor yellow a against septic cardiomyopathy: insights from integrated machine learning, WGCNA, and experimental validation.

UNLABELLED: Sepsis-induced cardiomyopathy represents a life-threatening complication arising from severe sepsis and septic shock. Hydroxysafflor yello...

Implementation of artificial intelligence to automate physical disector in a fractionator design for quantification of stem cell-derived neurons.

Accurate quantification of stem cell-derived dopaminergic neurons is essential for advancing cell therapy strategies in Parkinson's disease (PD). Trad...

The association between plasma IgG N-glycosylation and viral encephalitis in children: a hospital-based case-control study.

BACKGROUND: Viral encephalitis (VE) is an acute inflammatory disease caused by viral infection. Children are at a significantly higher risk of develop...

Breaking the culture habit: Complementing culture-based veterinary diagnostics with metagenomic data -A case study of feline and canine skin infections.

BACKGROUND: Skin infections have been described as the primary cause for veterinary small animal practice visits, frequently requiring topical and sys...