Parenting

Cardiovascular risks of plastic-associated chemicals: Integrating mixture modeling and SHAP-explained machine learning to unravel linear and non-linear associations.

INTRODUCTION: Plastic-associated chemicals (PACs) are widely detected environmental contaminants, yet their cardiovascular relevance in the context of concurrent exposure remains unclear. We evaluated individual and mixture-level associations of urinary PAC biomarkers with cardiovascular disease (CVD) status among U.S. adults. METHODS: We analyzed 3,831 adults from the National Health and Nutritio...

Multi-domain identification of myocardial infarction incidence using explainable AI: the overlooked role of periodontal health.

Myocardial infarction (MI) is a major global health concern influenced by diverse risk factors. Despite growing evidence of oral-systemic connections, current MI models largely exclude oral health indicators, reflecting the longstanding separation between dental and medical paradigms. This study introduces a multidomain, interpretable machine learning framework that integrates detailed periodontal...

Diffusion models for virtual populations and pharmacometric simulations.

To evaluate diffusion model-based artificial intelligence approaches for generating virtual populations with physiological determinants of drug dosing...

A Food Data-Nutrition Intelligence Framework to Support UK Food System Transformation.

This review explores current opportunities and challenges across data, health metrics, nutrition science, digital technology and policy in the context...

Navigating AI with pedagogical purpose: Toward an anatomy-centered framework for AI-enhanced learning.

Artificial Intelligence (AI) has emerged as a transformative force in medical education, enabling customized, feedback-rich, and immersive learning ex...

Development and validation of an interpretable machine learning model for predicting hypertension risk in patients with psoriasis.

OBJECTIVE: Hypertension is a common yet frequently underdiagnosed comorbidity in psoriasis patients. Early identification and blood pressure control a...

Applications of generative artificial intelligence in long-term care services: A systematic review of the evidence on efficacy for improving resident health related quality of life.

BACKGROUND: Generative artificial intelligence (GAI) has rapidly expanded into health and social care, offering new opportunities for communication, c...

Deep Learning Prediction of O-Glycopeptide Tandem Mass Spectra Enhances O-Glycoproteomics.

Protein glycosylation, a post-translational modification involving the attachment of glycans to proteins, plays critical roles in numerous physiologic...

Integrative multi-omics reveals NQO1-mediated airway epithelial injury as a key mechanism of bisphenol A-induced COPD.

Bisphenol A (BPA) is a ubiquitous environmental pollutant, but its relationship with chronic obstructive pulmonary disease (COPD) and the underlying t...

An interpretable ensemble learning framework for COPD classification using population-based clinical and laboratory data from NHANES.

INTRODUCTION: Chronic obstructive pulmonary disease (COPD) represents the third leading cause of death globally, affecting 213.39 million people, yet ...

Nursing as social control: An ethical perspective on care in dystopian contexts.

This article offers a comprehensive analysis of the representations of nursing and healthcare in contemporary and classic dystopian literature and fil...

Chemical-Sensing Catheters for Long-Term and Personalized Therapeutic Management.

Long-term intravenous catheterization is vital for delivering chemotherapy to cancer patients and parenteral nutrition to those with intestinal failur...

The Future of Imaging in Heart Failure: Toward Precision Phenotyping, Integration, and Intelligence.

PURPOSE OF REVIEW: Heart failure (HF) is increasingly understood not as a single, uniformly treated diagnosis but as a heterogeneous syndrome requirin...

AgriOptNet: A hybrid optimization and lightweight deep learning framework for soil texture classification and crop recommendation based on nutrition.

Agriculture is a central part of human subsistence, with classification of soil texture and nutrition-based crop recommendation being the central aspe...

Artificial intelligence-driven environments as emerging contexts in suicide risk.

Recent reports have described suicides temporally associated with artificial intelligence (AI)-mediated interactions, including conversational agents ...

ExposoGenomics: integrating genome and exposome as jointly dynamic systems for causal discovery and precision health.

The past decade has witnessed an unprecedented convergence of exposomic technologies, population-scale genomics, and AI-enabled data science, creating...

Advanced prediction of cardiovascular-kidney-metabolic syndrome using eight machine learning models and 24 composite indices.

AIM: This study aimed to construct and validate a machine learning classifier for cross-sectionally stratifying existing cardiovascular-kidney-metabol...

Defect engineered 2D MoS2 materials for ML-enabled SERS detection of neurotransmitters.

Mechanisms of neurotransmitter detection using a two-dimensional MoS2 platform are discussed. Machine learning methods are applied to distinguish the ...

Academics' Experiences and Perceptions of ChatGPT in Nutrition and Dietetics Education: A Qualitative Study.

BACKGROUND: Artificial intelligence (AI) tools such as ChatGPT are increasingly influencing health sciences education, prompting renewed attention to ...

Who is at high risk of poor diet quality? A precision public health nutrition approach using machine learning.

BACKGROUND: Suboptimal diet quality contributes to poor health. Numerous factors at all levels of the socioecological model intersect to influence ind...