Infectious Disease

Identifying the Most Important Influencing Factors Based on Demographic Information, Nutrition, Physical Activity, Leisure Time, and Underlying Diseases in the Severity of Disease in COVID-19 Patients Using Data Mining Techniques.

BACKGROUND AND AIMS: The COVID-19 pandemic has affected millions of individuals worldwide and resulted in substantial mortality. Data mining and machine learning techniques enable the analysis of comprehensive patient data, facilitating the identification of key patterns and determinants that support clinical and preventive decision-making. METHODS: This study evaluates the performance of three ma...

Interferon-Associated Antiviral Programs Define LAG-3+ Exhaustion-Like CD8+ T-Cell Remodeling in Influenza a Virus Infection: An Integrative Single-Cell and Multi-Cohort Analysis.

BACKGROUND: Influenza A virus (IAV) infection induces complex antiviral immune responses, yet how innate sensing, host genetic susceptibility, and adaptive immune dysfunction converge remains incompletely understood. This study investigated peripheral immune remodeling during IAV infection, focusing on LAG-3-expressing CD8+ T cells and their transcriptional and genetic signatures. METHODS: Single-...

Innovative approaches to therapeutic target discovery amid the global challenge of antimicrobial resistance.

Antimicrobial resistance is a constant threat to global public health, requiring innovative strategies for therapeutic target identification. Hence, t...

Quorum-sensing, microbiome interactions, and emerging artificial intelligence-assisted anti-virulence strategies in Salmonella Typhi: a critical review of translational opportunities and challenges.

Typhoid fever, caused by Salmonella enterica subsp. enterica serovar Typhi (Salmonella Typhi), remains a significant global health challenge that is i...

A radiology-aware fuzzy deep learning framework with entropy-guided feature selection for robust multi-disease chest X-ray classification across multiple magnifications.

Chest X-ray (CXR) imaging remains the most widely used and cost-effective modality for diagnosing thoracic diseases, yet automated multi-disease inter...

Recent advances in screening, diagnosis, prognosis and personalized treatment of sepsis.

Sepsis is a multi-system physiological syndrome defined as a dysregulated host response to infection. Despite recent advances clinicians continue to d...

A Generative Neuro-Symbolic AI for Protein Sequence Design.

Deep learning has revolutionized computational protein design, enabling the generation of sequences that fold onto target backbones with unprecedented...

Enterococcus faecium MMX derived from traditional fermented mare's milk alleviates colitis by modulating the LCN2-NLRP3 pyroptosis axis.

Ulcerative colitis (UC) is a relapsing inflammatory disorder of the intestine for which safe and effective therapeutic strategies are urgently needed....

Regulatory Approaches to Cybersecurity Risk Management for AI-Enabled Medical Device Software in Korea, the United States, and the European Union: Comparative Document Analysis.

BACKGROUND: Software-based and AI-enabled medical devices are increasingly networked and updatable, expanding the attack surface and making cybersecur...

EXPLAIN COVIDNET: EXPLAINABLE AI FOR TRANSPARENT AND RELIABLE X-RAY SCREENING.

Recently, deep learning has emerged as a prominent branch of AI, gaining attention for its high accuracy and wide-ranging application in various domai...

Bacterial triosephosphate isomerase as a therapeutic target, current knowledge and future perspectives: A review.

Triosephosphate isomerase (TIM) is a very efficient catalyst due to its precise dynamic architecture. Most of the structural, functional, and physicoc...

Promoter engineering in oleaginous yeasts for value-added chemical production.

Oleaginous yeasts, particularly Yarrowia lipolytica, are increasingly used as microbial platforms for producing lipids and other value-added compounds...

Psychoneuroimmunology-informed strategies for early detection of biological threat exposure: Insights from experimental rodent models.

The growing frequency of emerging infectious diseases, antimicrobial resistance, and accidental or deliberate biological threat releases underscores t...

Bifurcation and chaos design of radial basis neural network for predictive modeling of fractional double-strain HIV co-infection model with intercellular delays and stochastic effects.

The aim of the present study is to obtain the numerical solutions of the fractional double-strain HIV co-infection model with intercellular delays and...

Causal treatment effects of gait-analysis-informed surgery on the Gait Outcomes Assessment List in children with cerebral palsy.

AIM: To estimate the effect of surgery on parent-reported gait outcomes as measured using the Gait Outcomes Assessment List (GOAL) questionnaire in a ...

Spatial intensity modelling of ISIS-related attacks using random forest regression: A GeoAI-based analysis of GTD data (2012-2019).

Spatial information is of crucial importance to understanding terrorist attacks and for security applications. Conventional risk assessments of terror...

Effects of Deep Neural Network-Enhanced Hearing Aids on Categorical Perception of Mandarin Tones.

PURPOSE: This study empirically evaluated the impact of deep neural network (DNN)-based noise reduction in hearing aids on the categorical perception ...

Adaptive ventilation based on cough detection and localization for airborne infection control in vehicles.

Cough-generated pathogen-laden aerosols can lead to airborne transmission of infectious diseases inside vehicle cabins, where occupants share a confin...

Neonatal Bloodstream Infections: A Narrative Review on Diagnostic and Therapeutic Challenges and Prospects in Developing Countries.

BACKGROUND: Bloodstream infections (BSIs) pose a significant global health challenge, particularly in developing countries. Neonates are highly vulner...

From fragmented records to living evidence: health system-governed, artificial intelligence-driven, continuously updated real-world clinical data from Truveta.

OBJECTIVES: Real-world data (RWD) have historically suffered from fragmentation, delayed availability, variable data quality, and limited analytic uti...