Diet & Nutrition

Ensemble machine learning strategies for mineral prospectivity mapping under data scarcity.

Leveraging machine learning to identify gendered stereotypes and body image concerns on diet and fitness online forums.

The pervasive expectations about ideal body types in Western society can lead to body image concerns, dissatisfaction, and in extreme cases, eating disorders and other psychopathologies related to body image. While previous research has focused on online pro-anorexia communities glorifying the "thin ideal", less attention has been given to the broader spectrum of body image concerns or how emergin...

A novel framework for groundwater quality evaluation in industrial zone using unsupervised machine learning methods.

Population density, urbanization and industrialization are the rapidly increasing and it's causes severe damages to freshwater ecosystem. The present ...

Association of cardiovascular-kidney-metabolic syndrome stages with MASLD prevalence and liver fibrosis severity: evidence from traditional and machine learning approaches.

INTRODUCTION: Cardiovascular-Kidney-Metabolic (CKM) syndrome reflects the convergence of cardiovascular, renal, and metabolic disorders. Metabolic dys...

Multimodal MRI reveals hypothalamic structural-functional alterations associated with bone mineral density loss in postmenopausal women.

Emerging evidence implicates central nervous system dysregulation in the pathogenesis of osteoporosis. However, the role of hypothalamic subregions - ...

Advancing Precision Nutrition Through Multimodal Data and Artificial Intelligence.

Interindividual variability in metabolic responses to diets complicates the relationship between nutrition and metabolic health, which highlights the ...

Clinical impact of adopting an AI-driven opportunistic bone health screening software using routine X-ray.

OBJECTIVES: To evaluate the clinical impact of an artificial intelligence device, Rho, that opportunistically screens X-rays for low bone mineral dens...

Inflammation at the crossroads of reproduction: SIRI as a prognostic signature of female infertility in hybrid regression-machine learning models.

BACKGROUND: Female infertility is a critical global health concern, with a rising prevalence and significant psychosocial consequences. This study aim...

Artificial intelligence on opportunistic computed tomography for predicting vertebral fracture risk in women undergoing estrogen deprivation therapy for breast cancer.

PURPOSE: Fracture risk prediction in women exposed to hormone deprivation therapies (HDTs) for breast cancer is challenging, since bone mineral densit...

A Cross-Sectional Study Based on Deep Learning to Explore the Effect of Triglyceride/Glucose Index on Periodontitis: An Analysis Based on the Large NHANES Database.

PURPOSE: Periodontitis is a common chronic inflammatory disease closely associated with metabolic syndrome. The triglyceride-glucose (TyG) index is a ...

Proteomics-driven innovations in plant-based foods: Current advances, emerging technologies, and future perspectives.

Despite rapid market growth, plant-based foods such as meat analogs, plant-based milk, yogurt alternatives, and fermented products still fall short of...

Meta-analysis of the uncultured gut microbiome across 11,115 global metagenomes reveals a candidate signature of health.

The human gut microbiome is important for host health, yet over 60% of gut species remain uncultured and inaccessible to experimental manipulation. He...

Identification of Key Physicochemical Characteristics Which Influence Epithelial-to-Mesenchymal Transition of Lung Cells after Exposure to Engineered and Natural Stone Dusts via a Hybrid Machine Learning Approach.

Exposure to respirable and inhalable dust from engineered stone is linked to lung diseases such as silicosis and COPD, yet the physicochemical propert...

Prediction of metabolically healthy obesity based on dietary nutrients: a comparative analysis of six machine learning models with SHAP and LIME interpretation.

PURPOSE: The relationship between dietary nutrient intake and metabolically healthy obesity (MHO) remains poorly understood. This study aimed to const...

Cardiovascular Risk Assessment Tools in Chronic Kidney Disease.

Cardiovascular (CV) risk calculators estimate the likelihood of CV events by integrating factors such as age, sex, blood pressure, lipids, smoking, an...

Advances in the postoperative care of the liver transplant recipient.

PURPOSE OF REVIEW: Survival rates following liver transplantation now exceed 90% at one year. However, the patient group undergoing liver transplantat...

Factors Associated with Machine Learning-Based Predictions of Retinal Aging Using Teleretinal Screening Images from Patients with Diabetes.

PURPOSE: To identify factors associated with accelerated retinal aging based on machine learning predictions of age using fundus images from teleretin...

Explainable machine learning for depression risk prediction in adults with obesity: development of an online tool.

Predicting heavy metal distribution coefficient in global soil via machine learning: the effect of mineral heterogeneity.

Heavy metal adsorption by soil particles significantly influences its pollution risk in global soil. However, the global distribution of soil adsorpti...

Predicting Attrition in a Public Nutrition Education Program: A Machine Learning Approach.

OBJECTIVE: To develop a machine learning model to identify adult Expanded Food and Nutrition Education Program (EFNEP) participants at high risk of at...