Diet & Nutrition

Evaluation of Large Language Models for Mapping Dietary Data to Food Databases.

BACKGROUND: New food databases increasingly provide biochemical information not yet captured in standard food composition databases (FCDs). To enable precision nutrition, new methods are needed to map foods to these FCDs. OBJECTIVE: We sought to provide real-world ground truth (benchmark) datasets and evaluate the use of large language models (LLMs) to match foods reported in dietary data with foo...

Response to Letter to the Editor: Advancing Artificial Intelligence in Renal Nutrition: The Need for Culturally Adaptive, Equity-Focused Frameworks Beyond Retrieval-Augmented Generation.

Advancing Artificial Intelligence in Renal Nutrition: The Need for Culturally Adaptive, Equity-Focused Frameworks Beyond Retrieval-Augmented Generation.

Clinically actionable classification tool for childhood and adult atopic dermatitis via explainable AI: a retrospective cross-sectional study optimizing diagnostic accuracy.

BACKGROUND: Despite the critical role of early identification in managing atopic dermatitis (AD), current studies are limited by the absence of adult-...

AI-planned and robotic-assisted pedicle screw placement improves accuracy and reduces loosening in lumbar fusion for patients with low bone mass: a multicenter study.

OBJECTIVE: This study aimed to evaluate the effectiveness of artificial intelligence (AI)-based pedicle screw trajectory planning combined with roboti...

Target-driven machine learning-enabled virtual screening (TAME-VS) enables prioritization of AKR1C3 inhibitors.

Machine learning-guided virtual screening has the potential to accelerate early-stage drug discovery, but its practical utility is often limited by un...

Non-invasive imaging diagnostic techniques in metabolic dysfunction-associated steatotic liver disease: a roadmap for clinicians.

Metabolic dysfunction-associated steatotic liver disease (MASLD), previously termed nonalcoholic fatty liver disease (NAFLD), is the most prevalent ch...

Engagement with an AI- and CGM-Integrated Digital Health Platform Is Associated with Clinically Significant Weight Loss.

BACKGROUND: Obesity affects millions of U.S. adults and is linked to cardiometabolic disease. This study examined whether user engagement with the Sig...

Mapping the digital determinants of health: a machine learning analysis of YouTube narratives on child undernutrition in Pakistan.

BACKGROUND: The role of social media in in shaping the public perception of health crises is growing, yet we know little about the contribution of pla...

Opportunistic Screening Based on Computed Tomography in Musculoskeletal Radiology: How and Why.

With the rapid growth of the use of computed tomography, advances in artificial intelligence enable opportunistic screening, the systematic extraction...

Comparison of ChatGPT and dietitians in formulating diet plans and recommendations for patients with cardiometabolic diseases.

BACKGROUND: Artificial Intelligence (AI) is transforming personalized medicine, yet its efficacy constitutes a dynamic factor in the field of health a...

Retraction: Enhanced heart disease diagnosis and management: A multi-phase framework leveraging deep learning and personalized nutrition.

Modelling the impact of dietary diversity on child nutrition in Pakistan: a machine learning analysis with Shapley Additive exPlanations and Boruta interpretability.

BACKGROUND: Pakistan faces a serious challenge in malnutrition, as its core nutrition indicators and minimum dietary diversity remain below the recomm...

Smart feeding: the role of artificial intelligence and integrated nutrition platforms in the ICU.

PURPOSE OF REVIEW: Tremendous improvement in the use of artificial intelligence has opened new opportunities to analyze the data obtained from electro...

Mass cytometry reveals complex neutrophil heterogeneity in patients with severe sepsis.

RATIONALE: Sepsis is a state of life-threatening organ dysfunction in the setting of infection. It is biologically heterogeneous, as evidenced by whol...

Laser Light Scattering-Enhanced Deep Computer Vision Method for the Detection of Trace Mineral Oil in Vegetable Oils.

Mineral oil contamination in vegetable oils poses a serious threat to food safety and consumer health. In this study, we reported an on-site compatibl...

Synergistic effects of biochar from the co-pyrolysis of lignocellulosic biomass and typical biomasses: mechanism of action and key parameters.

Biomass waste is a promising renewable feedstock, and pyrolytic conversion into biochar brings prominent economic and environmental benefits. Co-pyrol...

Transforming hemodialysis care: a tripartite collaboration model among medical staff, AI agents, and robots.

Hemodialysis demand is rising as populations age and the chronic kidney disease burden increases, yet dialysis units face persistent workforce constra...

Evaluating a Multitask AI Model versus Humans for Portion Size Estimation.

BACKGROUND: Accurate dietary assessment is essential for precision nutrition and nutrition surveillance. Portion size estimation remains challenging, ...

Reconfiguring biofortification strategies to transform food systems and address micronutrient deficiency of the 21st century.

Despite achieving substantial progress in caloric food security, micronutrient deficiencies remain a major global health challenge, highlighting a per...