Public Health

Multidimensional analysis and predictive modeling of cognitive decline risk in the United States using propensity score matching and machine learning.

Cognitive decline, an early indicator of neurodegenerative disorders, presents a growing public health challenge. This study aimed to integrate causal inference and machine learning to quantify the causal impact of high-risk status on cognitive function, explore geographic and temporal heterogeneity, and develop predictive models for early identification of at-risk individuals in the United States...

A review of AI/ML approaches in wastewater surveillance advancement.

Wastewater-based epidemiology (WBE) has emerged as a powerful tool for early detection and monitoring of infectious diseases, particularly during pandemics such as COVID-19. This study systematically evaluates the application of artificial intelligence (AI) and machine learning (ML) models in WBE over the past five years, focusing on their effectiveness in pathogen detection and disease trend fore...

Using Artificial Intelligence Methods to Evaluate the Effect of the National Cytomegalovirus Awareness Month on the Content and Sentiment of Social Media Posts: Infodemiology Study.

BACKGROUND: The month of June has been recognized as the National Cytomegalovirus (CMV) Awareness Month since 2011 in the United States. Established b...

Evolving strategies may facilitate oral pathology and cancer surveillance, monitoring, and detection for patients at risk.

BACKGROUND: Oral cancers account for considerable morbidity and mortality worldwide, and their incidence has increased in the past several years, desp...

Vancomycin resistance in gram-positive infections: evolutionary strategies of survival.

Vancomycin is a critical glycopeptide antibiotic for treating severe infections caused by Gram-positive bacteria, particularly MRSA and Clostridioides...

Large Language Models Improve Scene Invariant Detection of Behaviours of Risk in Dementia Residential Care Across Multiple Surveillance Camera Views.

Behavioural and psychological symptoms of dementia pose challenges to the safety and well-being of individuals in residential care. The integration of...

Personalized surveillance in giant congenital melanocytic nevus, including the role of AI, histopathology and MC1R genotyping: A case report.

Giant congenital melanocytic nevi (GCMN) are rare pigmented skin lesions present at birth that carry an increased risk of malignant melanoma and neuro...

Assessing greenspace and cardiovascular disease risk through deep learning analysis of street-view imagery in the US-based nationwide Nurses' Health Study.

BACKGROUND: Living near greenspace is associated with decreased cardiovascular disease (CVD). Greenspace estimates, however, typically represent all t...

Microclimates, land cover, and socioeconomic vulnerability shape Anopheles hotspots in Maryland, USA.

BACKGROUND: Anopheles mosquitoes pose notable public health concerns as competent vectors of malaria and other diseases. Although malaria is no longer...

The use of artificial intelligence in decreasing vaccine skepticism and hesitancy.

PURPOSE OF REVIEW: Recent advances in artificial intelligence (AI) coincide with decreases in confidence in vaccines. This review examines studies tha...

Using artificial intelligence to advance pediatric infection prevention and control.

PURPOSE OF REVIEW: Recent literature describes the deployment of different artificial intelligence (AI) technologies to potentially support infection ...

Liver cancer risk stratification using deep learning on nationwide longitudinal health screening data: a retrospective cohort study.

BACKGROUND: Current liver cancer screening in Korea focuses on viral hepatitis or cirrhosis, despite rising risks from metabolic and alcohol-related l...

Charting exposomethics: a roadmap for the ethical foundations of the human exposome project.

BACKGROUND: The Human Exposome Project (HEP) aims to chart lifelong environmental exposures and their biological consequences, furnishing the environm...

A novel hypothetical protein (SAUSA300_1684) confers excellent protection against multi-drug-resistant Staphylococcus aureus infection in the murine model.

Staphylococcus aureus is a leading cause of nosocomial infections, including sepsis, bacteraemia, pneumonia, and endocarditis, and continues to pose a...

Using Latent Dirichlet Allocation Topic Modeling to Uncover Latent Research Topics and Trends in Renal Cell Carcinoma: Bibliometric Review.

BACKGROUND: Renal cell carcinoma (RCC) is a common, often lethal kidney cancer that originates in the renal cortex. Its incidence is rising, and major...

Predictive modeling and spatiotemporal analysis of TB in Argentina: Advancing control efforts through machine learning.

OBJECTIVES: To improve prediction and understanding of TB dynamics in Argentina, identifying key risk factors and high-incidence areas to inform surve...

Machine learning-based typing of Clostridium botulinum group III by FT-IR spectroscopy.

This study aimed to investigate the utility of Fourier-Transform Infrared Spectroscopy (FT-IRS) for differentiating Clostridium botulinum (C. botulinu...

A Comparative Study of Machine Learning Models for Identification of Antiviral Peptides Using Various Encoded Features.

Viruses are a significant threat to human life, as demonstrated by the global COVID-19 pandemic and the Ebola outbreak. Diseases such as smallpox, AID...

Predicting the Future Burden of Renal Replacement Therapy in Türkiye Using National Registry Data and Comparative Modeling Approaches.

BACKGROUND: Chronic kidney disease is a growing public health problem worldwide, and the number of patients requiring renal replacement therapy is ste...

Complex Interactions Between Stress, Nutrition, Gut Microbiota, and Infectious Diseases and Their Impact on Health in Global Conflicts: A Narrative Review.

Following the global recovery from the COVID-19 pandemic, wars and conflicts have escalated to levels unseen since the Cold War. It is well known that...