Infectious Disease

Structure-based identification of potential antifungal agents against Aspergillus fumigatus through multiscale computational approaches.

Fungal infections caused by Aspergillus fumigatus pose a serious clinical challenge, particularly in...

Rapid identification of carbapenem-resistant Acinetobacter baumannii based on MALDI-TOF mass spectrometry and machine learning.

BACKGROUND: Carbapenem-resistant Acinetobacter baumannii (CRAB) is a major pathogen in hospital-acqu...

Automated diagnosis of Helicobacter pylori infection from routine endoscopic images using deep learning: a development and validation study.

BACKGROUND: Real-time endoscopic diagnosis of Helicobacter pylori infection remains challenging and ...

From out-of-pocket to prepaid financing? projected health expenditure and financing mix in Egypt, 1995-2050.

BACKGROUND: Egypt's health financing is characterised by persistently high out-of-pocket (OOP) payme...

Machine learning discriminates bacterial, fungal, and viral infections using temporal blood analyte dynamics in bottlenose dolphins (Tursiops truncatus).

OBJECTIVE: To determine underlying infectious disease as bacterial, fungal, or viral in origin from ...

Clinical and laboratory characteristics associated with liver failure in hospitalized dengue patients: insights from a non-endemic region.

BACKGROUND: Dengue fever is an emerging public health issue expanding into non-endemic regions like ...

Patient centered and technology enabled strategies to improve Tuberculosis treatment adherence.

INTRODUCTION: Tuberculosis (TB) treatment adherence (how regular patients follow the prescribed medi...

Cascade Sensor Array Involving Nanozyme with Glycoside Hydrolase-like Activity for the Accurate Identification of Six Aminoglycosides.

Developed sensor arrays commonly rely on directly sensing the effects of antibiotics on oxidoreducta...

Enhancing clinical utility of AI-based antimicrobial resistance models: a perspective.

Machine learning-driven identification of virulence determinants in Borrelia burgdorferi associated with human dissemination.

Lyme disease, the most common tick-borne infectious disease in the United States, presents with high...

Deep learning-enabled discovery of antibiotics effective against Neisseria gonorrhoeae.

Neisseria gonorrhoeae is a common Gram-negative pathogen with increasing resistance to all recommend...

Identification of host gene transcripts by machine learning and their application to predict outcome in Ebola virus disease.

BACKGROUND: In humans, Ebola virus disease (EVD) has a high mortality rate. While viral load is a kn...

Engineering lignin-based antimicrobials: Experimental foundations and data-driven optimization.

Lignin is the most abundant naturally occurring phenolic polymers on Earth and represents a largely ...

Rapid screening of spreading-type Bacillus using a YOLO-based classifier on sheet media.

Aerobic spore-forming bacteria cause food poisoning and spoilage and can be distinguished from other...

Surface-enhanced Raman spectroscopy and machine learning based profiling of β-lactam antibiotic-induced biochemical responses in methicillin-resistant and methicillin-susceptible Staphylococcus aureus strains.

The global escalation of antimicrobial resistance in Staphylococcus aureus (S. aureus) necessitates ...

Hybrid deep learning-based rapid broad-Spectrum antimicrobial susceptibility prediction from whole-genome assemblies.

Antimicrobial resistance (AMR) is a global public health threat. Mortality and poor treatment outcom...

CellVision: A Deep Learning based Image Analysis Platform to Accelerate Immuno-Plaque Assay Data Processing for Dengue Vaccine Development.

Accurately detecting patterns of interest across a large number of images presents a significant cha...

Post-Pandemic Forecasting of Pediatric Acute Respiratory Infections with Deep Learning: A Multi-Pathogen, Multi-Time-Horizon Study.

BACKGROUND: Acute respiratory infections (ARIs) remain a major cause of morbidity and hospitalizatio...

Based on a radiomics-clinical nomogram to predict the therapeutic effect of pulmonary cryptococcosis pneumonia.

We aimed to develop a radiomics-clinical nomogram to predict the therapeutic effect of PC pneumonia....

Explainable machine learning reveals evolutionary signals in influenza haemagglutinin.

Identifying amino acid changes that lead to phenotypic change is critical to viral surveillance. Com...

Combining machine learning and iterative experiments to keep pace with emerging viral variants of concern.

Modeling and predicting viral mutations before they emerge plays a crucial role in pandemic prepared...