Infectious Disease

Deep learning identifies water bodies from low-cost drone images for mosquito larval habitat mapping.

Mosquito larval source management remains a critical strategy for malaria control, but traditional methods for mapping breeding sites are labor-intensive and slow. While drones offer a promising tool, their application is often hindered by reliance on costly orthomosaic generation (stitching drone images into precise, georeferenced maps) and multispectral sensors, creating significant barriers for...

Hybrid quantum-classical neural networks for real-time fault detection in power systems.

As modern power systems continue to be integrated with renewable energy sources, the ability to detect faults in these systems quickly and accurately is becoming more sophisticated. A Hybrid Quantum Classical Neural Network (HQCNN) model is presented in this paper that addresses the real-time fault detection challenge in transmission systems. A classical feature extractor, in this case a 1D CNN, a...

Intelligent automation cognitive system for accurate malaria diagnosis using digital blood smears.

Malaria is a potentially fatal illness caused by a parasite of the genus Plasmodium that humans get by being bitten by female Anopheles mosquitoes car...

Risk stratification for in-hospital mortality in sepsis-associated acute kidney injury patients receiving continuous renal replacement therapy: an interpretable, externally validated machine learning study.

Patients with sepsis-associated acute kidney injury (SA-AKI) requiring continuous renal replacement therapy (CRRT) have a high risk of in-hospital mor...

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-acquired infections, and rapid detection is critical f...

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 often requires biopsy-based testing, delaying trea...

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) payments exceeding 50% of total health expenditure and ...

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 longitudinal assessment of biochemistry and hemato...

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 Changsha, China. Liver involvement is a critical c...

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

INTRODUCTION: Tuberculosis (TB) treatment adherence (how regular patients follow the prescribed medication) has a major role in TB control. In high bu...

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 oxidoreductase-like activity, which has faced significant chal...

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 highly variable clinical outcomes, ranging from locali...

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

Neisseria gonorrhoeae is a common Gram-negative pathogen with increasing resistance to all recommended antibiotics. There is a critical need to improv...

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 known prognostic factor, it is not effective in pred...

From development to clinical practice: deployment of an interoperable and secure ML-based CDSS to aid in the early detection of sepsis.

Recent research has increasingly focused on machine learning (ML) models for early disease prediction, yet practical frameworks for integrating these ...

Development and validation of artificial intelligence-assisted volumetric response criteria in pleural mesothelioma (ARTIMES): a retrospective, multicohort, multicentre study.

BACKGROUND: Response evaluation in pleural mesothelioma is challenging because its crescent growth pattern is poorly captured by diameter-based criter...

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 underutilized renewable resource. Owing to its aro...

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 bacteria based on colony size and shape when grow...

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 rapid analytical tools to reliably distinguish bet...