Sepsis

Improving Hepatitis B outcome prediction with ensemble machine learning: A study on predictive models and interpretability.

OBJECTIVE: Hepatitis B virus (HBV) is a significant global health threat, responsible for severe liv...

Chemokine-like factor-like MARVEL transmembrane domain-containing 1 identified as a novel target protein for immune dysregulation in sepsis: A machine learning and molecular dynamics framework for diagnostic biomarkers and therapeutic exploration.

BACKGROUND: Sepsis, a systemic inflammatory response syndrome precipitated by infection, involves cr...

Psychedelics, entactogens and psychoplastogens for depression and related disorders.

Currently, the most actively investigated rapidly acting antidepressants, anxiolytics and/or anti PT...

Melioidosis molecular diagnostics: An update.

Melioidosis, a fatal tropical disease, presents a wide array of clinical manifestations, including a...

Deciphering the transcriptomic characteristic of lactate metabolism and the immune infiltration landscape in abdominal aortic aneurysm.

BACKGROUND: Abdominal aortic aneurysm (AAA) is a common degenerative vascular disease characterized ...

Identification of bacterial infection types in decomposition stages at various temperatures using pathology images and artificial intelligence algorithms.

Bacterial infections present a significant threat to human health, and accurate identification of in...

Author Correction: Machine learning for predicting device-associated infection and 30-day survival outcomes after invasive device procedure in intensive care unit patients.

Prediction of Antibiotic Resistance Phenotypes and Minimum Inhibitory Concentrations in Using Machine Learning Analysis of Its Pan-Genome and Pan-Resistome Features.

Traditional experimental methods for determining antibiotic resistance phenotypes (ARPs) and minimum...

Fixed-bed studies and artificial neural network modeling for removal of fluoroquinolone antibiotics using a green MWCNT@E adsorbent.

Ciprofloxacin (CIP) and ofloxacin (OFL), commonly used fluoroquinolone antibiotics, have been freque...

Clinical correlates of data-driven subtypes of deep gray matter atrophy and dopamine availability in early Parkinson's disease.

Recent machine-learning techniques may be useful to identify subtypes with distinct spatial patterns...

Exploring the molecular mechanisms of lactylation-related biological functions and immune regulation in sepsis-associated acute kidney injury.

Lactylation, a novel post-translational modification, has been implicated in various pathophysiologi...

Rapid prediction of antibiotic resistance in complex using whole-genome and metagenomic sequencing.

Clinical management and surveillance of the complex (ECC) face significant challenges due to inaccu...

28-day all-cause mortality in patients with alcoholic cirrhosis: a machine learning prediction model based on the MIMIC-IV.

To develop and validate a machine learning prediction model for 28-day all-cause mortality in patien...

A Mortality Risk Prediction Model for Septic Shock in Patients Aged ≥50: Role of Norepinephrine Index and Procalcitonin.

BACKGROUND: Septic shock is a high-mortality syndrome, particularly in patients aged 50 and older. P...

Similar Prophage Induction but Divergent Antibiotic Resistance Gene Occurrence: Leachates and Free Radicals Drive Differential Activation Mechanisms in Aged Tire Crumb Rubber.

Indigenous phages play a key role in the spread of extracellular antibiotic resistance genes (eARGs)...

Multimodal Wearable Sensing for Biomechanics and Biomolecules Enabled by the M-MPM/VCFs@Ag Interface with Machine Learning Pipeline.

The addition sensing device of sweat to wearable biostress sensors would eliminate the need for usin...

The future of healthcare-associated infection surveillance: Automated surveillance and using the potential of artificial intelligence.

Healthcare-associated infections (HAIs) are common adverse events, and surveillance is considered a ...

Predicting carbapenem-resistant Pseudomonas aeruginosa infection risk using XGBoost model and explainability.

The prevalence and spread of carbapenem-resistant Pseudomonas aeruginosa (CRPA) is a global public h...

Multi-omics profiling of cross-resistance between ceftazidime-avibactam and meropenem identifies common and strain-specific mechanisms in clinical isolates.

is a highly versatile and resilient pathogen that can infect different tissues and rapidly develop ...

Machine learning models for predicting severe acute kidney injury in patients with sepsis-induced myocardial injury.

Severe acute kidney injury (sAKI) is a prevalent and serious complication among patients with sepsis...

A machine learning-based prediction model for sepsis-associated delirium in intensive care unit patients with sepsis-associated acute kidney injury.

Sepsis-associated acute kidney injury (SA-AKI) patients in the ICU often suffer from sepsis-associat...