Infectious Disease

Harnessing Artificial Intelligence to Strengthen Acute and Critical Care Nursing Practice: A Systematic Review.

BACKGROUND: Artificial intelligence (AI) is reshaping clinical decision support systems (CDSSs). In acute and critical care, nurses provide continuous surveillance, recognise deterioration, coordinate escalation and translate protocols into bedside action. AI-CDSS may be particularly relevant when they support rather than replace clinical judgement. AIM: To examine whether nurse-used AI-CDSS impro...

Exploring Emotional Attachment to Socially Assistive Robots: A Qualitative Study Among Older Adults.

Socially assistive robots (SARs) show potential to alleviate loneliness among older adults but raise ethical risks regarding emotional attachment. While existing studies largely focus on normative frameworks, empirical insights into older adults' subjective experiences in specific cultural settings remain limited. Grounded in China's care realities, this qualitative study explored older adults' an...

Retraction notice to Letter in reference to "Using machine learning for personalized prediction of longitudinal COVID-19 vaccine responses in transplant recipients" [AJT Volume 25, Issue 5, May 2025, Pages 1138-1139].

Development and Validation of an Interpretable Machine Learning Model for Predicting ICU-Acquired Weakness in Postoperative Patients.

BACKGROUND: ICU-acquired weakness (ICU-AW) is a common and debilitating complication among critically ill patients, particularly those undergoing majo...

Recent Mycobacterium tuberculosis Transmission, United States, 2018-2022 (Response).

Recent Mycobacterium tuberculosis Transmission, United States, 2018-2022.

Cross-tissue immune profiling of APOE ε4 reveals early dysregulation in Alzheimer's disease.

INTRODUCTION: Apolipoprotein E (APOE) ε4 is the strongest genetic risk factor for late-onset Alzheimer's disease (AD), but its contribution to disease...

An Interpretable Machine Learning Approach to Ecologically Characterize Soil Carbon and Structure From Multi-Kingdom Microbiome, Texture and Climate.

Soil physical structure is a critical determinant of agricultural landscape resilience, yet standard pedotransfer functions estimate soil hydraulic an...

Artificial intelligence-assisted design of MAGE-A4 ×CD16 T-cell receptor-like natural killer cell engagers.

The cancer-testis antigen MAGE-A4 is an attractive immunotherapy target due to its high expression in various malignancies and restricted expression i...

Artificial intelligence in emergency medicine: from algorithmic performance to real-world clinical integration - understanding the implementation gap.

BACKGROUND: Emergency departments (EDs) operate under time pressure, diagnostic uncertainty, and cognitive overload. Artificial intelligence (AI)-driv...

Integrating Microfluidics Chips into Vector-Borne Disease Surveillance: Technological Breakthroughs and Persistent Hurdles.

BACKGROUND: Vector-borne diseases (VBDs), such as malaria, dengue, and Zika virus infections, remain a critical global health burden, particularly in ...

GANs in Peptide Drug Discovery: From De Novo Design to Multi-Property Optimization and Clinical Translation.

Peptide drugs are vital for treating intractable diseases, yet traditional discovery is limited by huge sequence space and poor pharmacokinetics. Gene...

A cross-species drug-discovery platform to accelerate the identification of lifespan-extending interventions.

We develop an integrated, high-throughput platform to evaluate pharmacological lifespan-extending interventions across five model organisms spanning u...

Redundancy-aware AI-guided discovery and experimental validation of antimicrobial peptides for infected wound treatment.

Artificial intelligence (AI) is accelerating antimicrobial peptide (AMP) discovery, but prediction-centered workflows often overlook dataset redundanc...

Early-Life Exposure to Organophosphorus Pesticide Mixtures and Impaired Neonatal Neurodevelopment: A Cohort Study Integrating Comprehensive Multi-Omics and Machine Learning.

Early-life exposure to low-dose organophosphorus pesticide (OPP) mixtures and their impact on neonatal neurodevelopment remain insufficiently characte...

A genomic catalog of Earth's bacterial and archaeal symbionts.

Microbial symbiosis drives the functional and phylogenomic diversification of life on Earth yet remains underexplored because of culturing challenges....

Prospective economic evaluation of a predictive artificial intelligence model for sepsis: Effects on hospital costs and return on investment.

Early sepsis detection is essential for improving outcomes and reducing costs, but traditional rule-based systems have limited accuracy and real-world...

A data-driven approach to hepatitis C forecasting using machine learning and epidemiological models.

The hepatitis C virus is a significant global health concern and a major cause of chronic liver disease. Therefore, developing a mathematical model is...

Artificial intelligence in Latin American hepatology: current evidence, implementation barriers, and strategic priorities.

Chronic liver diseases are an increasing cause of morbidity and mortality in Latin America, driven by the convergence of alcohol and metabolic-associa...

Development of a machine-learning risk stratification tool for vasoactive medication need after two-bolus fluid resuscitation in pediatric suspected sepsis.

BACKGROUND: Timely vasopressor initiation is critical in fluid-refractory pediatric septic shock, yet clinicians lack objective tools to identify chil...