Latest AI and machine learning research in diet & nutrition for healthcare professionals.
OBJECTIVE: Adiposity rebound (AR), the second rise in BMI during growth, increases the risk of obesity and metabolic diseases when it occurs early. We aimed to identify key factors influencing early AR (EAR) within two critical 1000-day periods and develop a predictive model. METHODS: Based on the Ma'anshan Birth Cohort (MABC), we collected serial BMI from birth through school age and applied line...
Regular physical activity (PA) remains challenging for many people with high cardiovascular risk and established cardiovascular disease (CVD). We aimed to study correlates of PA behaviour in a population sample with increased cardiovascular risk and established CVD in Austria. We analysed cross-sectional data from the Paracelsus 10,000 study, a population-based cohort study of 40-70-year-olds in t...
BACKGROUND: Personalized meal planning by registered dietitian nutritionists (RDNs) is time-intensive. Large language models (LLMs) may automate draft...
Precision nutrition on a global scale necessitates an understanding of food not as static collections of so-called macronutrients but rather as dynami...
BACKGROUND: Artificial intelligence applications have been developed to predict the nutrient content of meals. However, none have been evaluated in th...
BACKGROUND: Gestational diabetes mellitus (GDM) is a common pregnancy complication, yet its molecular mechanisms remain incompletely understood. This ...
BACKGROUND: AI-driven clinical systems can improve diagnosis, prognosis, and resource allocation, but they may reproduce disparities encoded in histor...
The coronavirus 2019 pandemic disrupted food purchasing behaviours, triggering both short- and long-term nutritional shifts. Here, analysing 9,367,550...
The high-altitude and unique climatic conditions of Tibet can have a significant impact on the growth and development of local children and adolescent...
UNLABELLED: AI-derived opportunistic screening using routine chest radiographs was evaluated in 6,028 adults and internally validated against DXA in a...
PURPOSE OF REVIEW: People with HIV (PWH) are increasingly susceptible to excess weight gain and obesity after initiation of antiretroviral therapy. Ho...
A dual-layer flat panel detector (DFD) allows for the acquisition of dual-energy images with a single x-ray exposure without scanning. In this paper, ...
BACKGROUND: Despite the effectiveness of lifestyle multidisciplinary (LMD) weight loss interventions in pediatric obesity, outcomes remain variable be...
OBJECTIVE: Stress and obesity are major health concerns affecting individuals worldwide. Artificial Intelligence (AI) is being designed to identify an...
BACKGROUND: Overactive bladder (OAB) is a prevalent condition, particularly among women, characterized by urinary urgency, often accompanied by freque...
PURPOSE: Clear guidelines on using dual-energy X-ray absorptiometry (DXA) are lacking. DXA-derived phenotypes based on whether the person was above or...
Childhood anemia remains a major public health challenge in Sub-Saharan Africa, adversely affecting physical growth, cognitive development, and child ...
BACKGROUND: Prior obesity neuroimaging studies used univariate methods and small samples, limiting reproducibility. Employing a large-scale dataset an...
BACKGROUND: Digital health technologies are transforming healthcare. There is limited research describing how these technologies have been applied by ...
Obesity in children and adolescents is rising in China and globally, with health consequences that are already evident during childhood. This Viewpoin...