Bacterial Infection

Interpretable four-factor day-1 nomogram for predicting sepsis-associated encephalopathy in septic ICU patients with AKI: Development and internal validation in MIMIC-IV.

Sepsis-associated encephalopathy (SAE) is common in the intensive care unit (ICU) and portends worse...

Predicting vesicoureteral reflux outcomes using artificial intelligence: A critical appraisal using APPRAISE-AI.

Vesicoureteral reflux (VUR) is a common congenital urinary tract anomaly in children, associated wit...

Prediction of death in burn patients infected with antibiotic-resistant Staphylococcus aureus using machine learning based techniques.

Artificial intelligence and predictive analytics in obstetric anesthesia: early warning for maternal complications.

PURPOSE OF REVIEW: Maternal morbidity and mortality remain largely preventable, yet current risk-ass...

Comparison and validation of multiple machine learning algorithms for predicting MDRO infection in catheter-related bloodstream patients: a multicenter cohort study.

UNLABELLED: Early identification of patients at high risk for multidrug-resistant organism (MDRO) in...

Deep Temporal Sequence Classification and Mathematical Modeling for Cell Tracking in Dense 3D Microscopy Videos of Bacterial Biofilms.

Automatic cell tracking in dense environments is plagued by inaccurate correspondences and misidenti...

Strategies for Safer Cefepime Use to Prevent Neurotoxicity Using the Electronic Health Record.

Cefepime, a cornerstone antibiotic in critical care, is associated with underrecognized cefepime-ind...

Unveiling hidden variables in stressed bacteria.

Phenotypic heterogeneity is a defining feature of bacterial stress responses, long framed as irreduc...

Mechanism of Ag+-Induced Folding of a Bacterial Peptide from Replica-Exchange Molecular Simulations.

Interactions between proteins and metal cations are central to biochemical processes and shape prote...

Practical machine learning model for early and accurate prediction of disseminated intravascular coagulation before its progression to an overt stage.

BACKGROUND AND AIMS: In patients with sepsis, anticoagulant therapy is expected to have maximal effi...

Novel convolutional neural network for bacterial identification of confocal microscopic datasets.

Artificial intelligence (AI), complex mathematical algorithms, is currently employed across various ...

Rare microbial taxa as potential drivers of yield variation in sauce-flavor baijiu fermentation: Insights from microecology and machine learning.

The multi-round, solid-state fermentation process of sauce-flavor baijiu exhibits substantial fluctu...

Smartphone-integrated molecularly imprinted sensor with convolutional neural networks for on-site detection of Norfloxacin.

We developed a portable sensing platform that integrates a dual-emission molecularly imprinted fluor...

From clinics to the environment: A systematic review of machine learning and MALDI-TOF MS in the identification of antimicrobial-resistant bacteria.

As a result of the increasing prevalence of Antibiotic-resistant bacteria (ARB) and antibiotic-resis...

AMP-CapsNet: a multi-view feature fusion approach for antimicrobial peptide prediction using capsule networks.

Antimicrobial peptides (AMPs) are universally found in both intracellular and extracellular settings...

Development of surface enhanced Raman spectra coupled with machine learning analysis for differentiation of closely related species within Enterobacter cloacae complex.

Artificial Intelligence Platform EnzySFC for Enzyme Screening and Functional Conversion: Completely Redirecting Nitrilase to Nitrile Hydratase Function.

Catalytic promiscuity provides fundamental insights into enzyme evolution. To address the multiobjec...

A machine learning model for predicting 28-day mortality in patients with alcoholic cirrhosis and sepsis: a study based on the MIMIC-IV database.

OBJECTIVE: To develop and validate the best machine learning model for predicting 28-day mortality i...

Enhancing Anesthetic Depth Assessment via Unsupervised Machine Learning in Processed Electroencephalography Analysis: Novel Methodological Study.

BACKGROUND: General anesthesia comprises 3 essential components-hypnosis, analgesia, and immobility....

Revitalizing actinobacteria research: an urgent response to the antimicrobial resistance crisis.

The crisis of antimicrobial resistance (AMR) is escalating while the antibiotic pipeline remains sta...

Iatrogenic plasticizer Di(2-ethylhexyl) phthalate (DEHP) exposure increases Sepsis mortality risk: Machine learning implicates monocyte-driven immune dysregulation.

Sepsis poses a significant global health burden, and ICU patients are disproportionately exposed to ...