Diet & Nutrition

ChatGPT for obesity management: a review of evidence, potential challenges, and clinical implications.

The global rise in the prevalence of obesity highlights the need for accessible and effective solutions for obesity management. ChatGPT, one of the fastest-growing artificial intelligence (AI) tools, is gaining attention for its potential to offer interactive support in managing complex conditions such as obesity. In this Review, we used a thematic synthesis approach to examine ChatGPT's effect on...

Exposome-wide patterns predict brain health in aging.

Promoting brain health is vital for well-being and reducing healthcare burdens. Brain health as measured with the Brain Age Gap (BAG) - the difference between chronological and predicted brain age- relates to many factors. However, a holistic view, integrating the range of factors an individual brain is exposed to, is missing for understanding how the exposome shapes brain health. After computing ...

Regulatory risk loci link disrupted androgen response to the pathophysiology of polycystic ovary syndrome.

A major challenge in deciphering the complex genetic landscape of polycystic ovary syndrome (PCOS) lies in the limited understanding of how susceptibi...

Machine Learning and Artificial Intelligence in Nutrition Research: Analytical Methods, Applications, and Key Considerations.

Nutrition research is increasingly utilizing artificial intelligence (AI) and machine learning to address analytical challenges posed by high-dimensio...

Objective prediction of siesta based on machine learning and association with obesity.

OBJECTIVES: To predict siesta behavior using machine learning models trained on self-reported and objective data-temperature (T), activity (A), positi...

Quantification of Soil Organic Carbon by Shifted-Excitation Raman Difference Spectroscopy with Machine Learning and Common Mode Rejection.

Soil organic carbon (SOC) is an important indicator of soil health and productivity in agricultural and natural ecosystems. Conventional measurement t...

Co-occurrence patterns of malnutrition indicators among children in sub-Saharan Africa.

BACKGROUND: Despite progress towards SDG2, malnutrition remains a major concern. Little is known about co-occurrence patterns of nutritional deficits,...

Predicting Osteoporosis Risk from Knee Radiographs and Clinical Features through Deep Learning: A Multimodal Approach.

BACKGROUND: Osteoporosis is a prevalent skeletal disease with high morbidity rates in developing countries due to limited access to gold-standard dual...

Why we need to maintain a critical view on big data and artificial intelligence predictions.

Artificial intelligence (AI) and machine learning are widely promoted as transformative tools for medical practice, yet their impact in daily rheumato...

Opportunistic Screening on Chest CT, From the AJR Special Series on Screening.

The increase in chest CT volumes affords radiologists the opportunity to systematically assess imaging biomarkers, including coronary and thoracic art...

Health Prediction Using Hybrid Deep Learning Models: A Transparent and Interpretable Approach.

Obesity has become alarming globally, with mounting health emergencies related to a number of chronic conditions like cardiovascular disease, diabetes...

An Expedited Chart Review Process for Large Database Studies Using Natural Language Processing and Multiwave Adaptive Sampling.

BACKGROUND: One of the ways to enhance analyses conducted with large claims databases is by validating the measurement characteristics of the code-bas...

Data-Driven Tooth Selection Enhances Partial-Mouth Periodontal Screening.

The high prevalence of periodontitis has imposed a significant global disease burden. Epidemiologic surveys rely on full-mouth periodontal examination...

Beyond Weight: Systems Biology and Precision Medicine Redefine Obesity as a Multidimensional Disease.

BACKGROUND: Traditional weight-centered models do not fully capture the biological complexity of obesity. Systems biology offers a new framework by in...

Associations between digital healthy diet literacy, artificial intelligence attitudes, mediterranean diet adherence, and health-related quality of life in adults.

Enhancing prediabetes and diabetes detection through a machine learning-enabled self-assessment approach.

OBJECTIVES: Reliable, accessible, noninvasive self-assessment screening for prediabetes/diabetes is lacking, leading to missed opportunities for early...

Association Between Environmental Chemicals Phthalates and Stroke Among the US Adults: A Cross-Sectional Study.

Stroke has a multifactorial etiology, and phthalates, as widely used environmental chemicals, may play an underexplored role in cerebrovascular health...

Application of machine learning algorithm for predicting acute malnutrition among under 5 children in east Africa using recent DHS.

Acute malnutrition remains a critical public health challenge across East Africa, contributing substantially to under-five morbidity and mortality. Ea...

From predictive accuracy to clinical utility: Model interpretability and the missing bone mineral density data.

This letter to the editor commends the study by Liu et al. on their machine learning model for predicting rib fractures but highlights two crucial cha...

Prediction model for frailty risk in ischemic stroke patients: Application and validation of support vector machines and nomograms.

This study aimed to develop a prediction model based on nomograms and support vector machines (SVM) to assess frailty risk in ischemic stroke patients...