Parenting

Unveiling the relationship between stress-hyperglycemia ratio and cardiometabolic multimorbidity risk using interpretable machine learning.

BACKGROUND: Cardiometabolic multimorbidity (CMM) is the simultaneous manifestation of multiple cardiovascular and metabolic diseases, and it has arisen as a substantial worldwide healthcare issue. The stress-hyperglycemia ratio (SHR) represents a novel biomarker that is strongly associated with the prognosis of various diseases; however, its role in CMM remains insufficiently understood. This rese...

Exploring artificial intelligence literacy's role in healthy behaviors and mental health.

Healthy behavior has long been linked to mental health outcomes. However, the role of artificial intelligence (AI) literacy in shaping healthy behaviors and its potential impact on mental health remains underexplored. This paper presents a scoping review offering a novel perspective on the intersection of healthy behaviors, mental health, and AI literacy. By examining how individuals' understandin...

Association of depressive symptoms with systemic immune-inflammation index and platelet parameters among survivors of myocardial infarction: a cross-sectional NHANES study enhanced by machine learning and SHAP analysis.

BACKGROUND: Inflammation is implicated in the elevated risk of depressive disorder following myocardial infarction (MI), with platelets serving as a k...

Evaluation of large language models in nutrition risk screening: a comparative analysis across 8 LLMs based on real-world EHR datasets.

Deconstruction by C. thermocellum-from microbe mediated to dynamic redistribution of cellulosomes.

Clostridium thermocellum is one of the most efficient microorganisms for the deconstruction of cellulosic biomass. To achieve this high level of cellu...

Automated underwater imaging system for continuous biofouling assessment.

Traditional antifouling coating evaluations rely on manual sample retrieval, imaging and subjective visual assessments, which are labour-intensive and...

[Emphasizing evolution of key technological elements in reconstructive surgery].

Reconstructive surgery is fundamentally dedicated to restoring tissues and organs damaged by trauma, disease, or congenital anomalies, with the goal o...

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...

Characterising symptom clusters: examining profiles of somatic symptoms and their psychosocial predictors among chinese youths using longitudinal data with a machine learning approach.

OBJECTIVE: Somatic symptoms (SS) pose public health burdens, but it remains unclear whether SS should be defined by overall severity or specific sympt...

Prediction and interpretability analysis of the properties of energetic ionic salts based on machine learning.

As a significant subset of energetic materials, energetic ionic salts (EISs) have garnered considerable attention due to their potential application i...

A machine learning study of the predictors of fear of happiness in Turkey and the USA.

OBJECTIVE: To identify key predictors of Fear of Happiness (FOH) by examining 22 psychological and demographic variables in Turkish and American sampl...

Oral-Rinse-Sourced Microbiota in Oral Health and Diseases in a Representative US Adult Population: Implications for Diagnostics.

AIMS: To investigate the associations between oral-rinse microbiota and distinct oral conditions, and further evaluate its potential ability to distin...

A comparative study of ordinal logistic regression and machine learning models for predicting women's malnutrition in bangladesh: evidence from BDHS 2022.

Malnutrition, including both undernutrition and overnutrition, remains a major public health concern in Bangladesh, particularly among women of reprod...

Nano-AI synergy in food chemistry: smart analytical tools for quality, safety, and nutritional profiling.

The convergence of nanotechnology and artificial intelligence (AI) is revolutionizing the landscape of food chemistry, quality control, and nutritiona...

Cascade machine learning reveals the regulatory mechanism of dissolved organic matter on nanoparticles aggregation behavior.

The aggregation of nanoparticles (NPs) in aquatic environments is influenced by multiple environmental conditions, with dissolved organic matter (DOM)...

A multi-target therapeutic framework for Alzheimer's disease: an integrative mechanistic review.

BACKGROUND: Alzheimer's disease (AD) is increasingly recognized as a multifactorial network disorder in which amyloid and tau pathology interact with ...

Immunoprotective and neuroprotective properties of gut microbiome in psoriasis.

Psoriasis impacts nearly 100 million people globally and is associated with neuropsychiatric comorbidities such as depression and anxiety. With gut mi...

Inferring high-fat dietary patterns from electronic health record data using machine learning.

OBJECTIVES: Electronic health records (EHRs) rarely capture dietary detail, limiting diet-disease research. We aimed to develop machine learning (ML) ...

A deep learning mobile application for tomato leaf nutrition deficiency identification with YOLOv8 and enhanced augmentation.

Nutritional deficiencies in crops lead to significant yield losses. Early and accurate detection of these deficiencies is crucial for effective interv...

Risk stratification using inflammatory and metabolic biomarkers: A multi-cohort predictive study of mortality in atherosclerotic cardiovascular disease.

BACKGROUND: The pathological process of atherosclerotic cardiovascular disease (ASCVD) involves complex interactions between metabolic dysregulation a...