Infectious Disease

Development and validation of a predictive model for profiling antibiotic resistance phenotypes of Acinetobacter baumannii strains via clinical MALDI-TOF mass spectra: A multicenter study.

Acinetobacter baumannii is a significant pathogen responsible for healthcare-acquired infections (HAIs), posing challenges due to its rising resistance to multiple antibiotics. Traditional diagnostic methods like bacterial cultures and antibiotic susceptibility testing (AST) are slow, necessitating the development of faster alternatives. This study aimed to create a predictive model for antibiotic...

AI-driven, low-cost aids for people with visual impairment.

PURPOSE OF REVIEW: The rapid integration of artificial intelligence (AI) into mainstream consumer devices has created new opportunities for accessible, low-cost support for individuals with visual impairment. This review examines emerging AI-driven tools that repurpose common hardware - such as smartphones and smart glasses - to deliver assistive functions traditionally reliant on costly, speciali...

Balancing Innovation in Artificial Intelligence With Practical Sepsis Definitions.

Operationalizing Sepsis Definitions With Artificial Intelligence: Toward Smarter Antibiotic Use.

EXPRESS: A Sentiment Analysis Study for Reflecting Society Insights on COVID-19 Vaccine Mid-Term Side Effects.

Social media discourse has the capacity to influence public perceptions of health-related issues. Understanding how vaccine side effects are discussed...

Microbial fermentation of cereals: nutritional, techno-functional, and compositional transformations toward data-driven process optimization.

Cereal fermentation represents a cornerstone of food bioprocessing that transforms staple grains into nutrient-dense, functionally enhanced ingredient...

Discovery of H2 Receptor Antagonists as Colistin Enhancers by Targeting Acid Stress Response.

Plasmid-mediated colistin resistance gene mcr has markedly diminished the effectiveness of colistin in managing multidrug-resistant (MDR) Gram-negativ...

Integrative computational and experimental identification of marine bacterial acetylcholinesterase inhibitors against alzheimer's disease.

Alzheimer's disease (AD) is a powerful neurodegenerative disease characterized by cholinergic deficiency, where the inhibition of acetylcholinesterase...

The chemical design of antimicrobial ionic liquids guided by machine learning: a review on balancing efficacy and toxicity.

The design of new antimicrobial materials is a critical challenge in chemistry and materials science, driven by the global threat of multidrug-resista...

A machine learning model for prediction of early-onset neonatal sepsis in low-income and middle-income countries: development and validation study.

OBJECTIVE: Early-onset sepsis (EOS), which occurs within the first 72 hours of life, can often be fatal for neonates. Machine learning (ML) models dem...

Machine learning approaches to predict the risk of tuberculosis among household contacts of index TB patients in Central Ethiopia.

Applied immunoinformatics in modern vaccine design: a comprehensive review of available computational tools.

The rapid evolution of computational biology has transformed vaccine design from a largely empirical process into a rational, data-driven discipline. ...

Specific diagnostic model for bacterial pneumonia constructed by combining multiple omics and multi machine learning models.

Due to the difficulty in quickly discriminating bacterial pneumonia (BPs) from pneumonia caused by other pathogens in clinic, the research for new bio...

Metabolic engineering of microorganisms for the valorization of C2 feedstocks.

This review summarizes recent advances in the metabolic engineering of microorganisms for the valorization of C2 feedstocks into high-value chemicals ...

Harnessing artificial intelligence for antimicrobial discovery and optimization.

The rise of antimicrobial-resistant pathogens has outpaced the traditional methods of drug discovery and development, emphasizing a need for new and i...

Antiviral drug discovery and development: challenges and future directions.

The coronavirus disease 2019 (COVID-19) pandemic has stimulated extensive endeavors toward the development of therapeutic interventions targeting seve...

Integrated virtual screening, machine learning and molecular dynamics identify novel phytochemical FabI inhibitors against MRSA.

Methicillin-resistant Staphylococcus aureus (MRSA) infections pose a critical global health threat, necessitating the discovery of novel antibacterial...

A Surface-Enhanced Raman Scattering-Digital Microfluidics Biosensing Platform Integrated with a 1D-Convolutional Neural Network for Noninvasive Detection of Inflammation Markers.

The noninvasive detection of multiple inflammatory markers (IMs) for early sepsis diagnosis is challenging. Therefore, herein, we innovatively develop...

Beyond pre-travel risk assessment: machine learning for clinical diagnosis in returned travellers.

Machine learning (ML) applications in post-travel clinical care remain limited. ML-based models show good diagnostic performance for malaria when clin...

Predicting low oxygen in patients with acute COVID-19 infection isolating at home: a clinical prediction model.

RATIONALE: Identifying patients who could be safely managed at home versus those needing hospitalisation was a particular concern during early COVID-1...