Primary Care

Diet & Nutrition

Latest AI and machine learning research in diet & nutrition for healthcare professionals.

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Showing 169-189 of 2,552 articles
Machine learning for predictive mapping of exceedance probabilities for potentially toxic elements in Czech farmland.

For efficient decision-making and optimal land management trajectories, information on soil properti...

Improving machine learning models through explainable AI for predicting the level of dietary diversity among Ethiopian preschool children.

BACKGROUND: Child nutrition in Ethiopia is a significant concern, particularly for preschool-aged ch...

Machine learning analysis of cardiovascular risk factors and their associations with hearing loss.

Hearing loss poses immense burden worldwide and early detection is crucial. The accurate models iden...

Comparative analysis and investigation of ultrasonication on juice yield and bioactive compounds of kinnow fruit using RSM and ANN models.

Ultrasonication (US) is a promising non-thermal technique widely applied in the food sector for impr...

AI-Assisted Label-Free Monitoring Bone Mineral Metabolism on Demineralized Bone Paper.

Effective drug development for bone-related diseases, such as osteoporosis and metastasis, is hinder...

Improving Dietary Supplement Information Retrieval: Development of a Retrieval-Augmented Generation System With Large Language Models.

BACKGROUND: Dietary supplements (DSs) are widely used to improve health and nutrition, but challenge...

The impact of multi-modality fusion and deep learning on adult age estimation based on bone mineral density.

INTRODUCTION: Age estimation, especially in adults, presents substantial challenges in different con...

Life's Crucial 9 and NAFLD from association to SHAP-interpreted machine learning predictions.

Non-alcoholic fatty liver disease (NAFLD) is the most prevalent chronic liver disease worldwide. Car...

Artificial intelligence in anti-obesity drug discovery: unlocking next-generation therapeutics.

Obesity, a multifactorial disease linked to severe health risks, requires innovative treatments beyo...

Obesity classification: a comparative study of machine learning models excluding weight and height data.

OBJECTIVE: Obesity is a global health problem. The aim is to analyze the effectiveness of machine le...

ChatGPT-4o and 4o1 Preview as Dietary Support Tools in a Real-World Medicated Obesity Program: A Prospective Comparative Analysis.

BACKGROUND/OBJECTIVES: Clinicians are becoming increasingly interested in the use of large language ...

Assessing the Links Between Artificial Intelligence and Precision Nutrition.

PURPOSE OF REVIEW: To conduct an overview of the potentialities of artificial intelligence in precis...

Social and economic predictors of under-five stunting in Mexico: a comprehensive approach through the XGB model.

BACKGROUND: The multifaceted issue of childhood stunting in low- and middle-income countries has a p...

Automated Fast Prediction of Bone Mineral Density From Low-dose Computed Tomography.

BACKGROUND: Low-dose chest CT (LDCT) is commonly employed for the early screening of lung cancer. Ho...

A Novel Mouse Model of Type 2 Diabetes Using a Medium-Fat Diet, Fructose, and Streptozotocin to Study the Complications of Human Disease.

The study of type 2 diabetes mellitus (T2DM) pathophysiology relies mainly on the use of animal mode...

Deep learning-based evaluation of panoramic radiographs for osteoporosis screening: a systematic review and meta-analysis.

BACKGROUND: Osteoporosis is a complex condition that drives research into its causes, diagnosis, tre...

Identifying individuals at risk for weight gain using machine learning in electronic medical records from the United States.

AIMS: Numerous risk factors for the development of obesity have been identified, yet the aetiology i...

PrOsteoporosis: predicting osteoporosis risk using NHANES data and machine learning approach.

OBJECTIVES: Osteoporosis, prevalent among the elderly population, is primarily diagnosed through bon...

deep-Sep: a deep learning-based method for fast and accurate prediction of selenoprotein genes in bacteria.

Selenoproteins are a special group of proteins with major roles in cellular antioxidant defense. The...

Machine Learning Models Integrating Dietary Indicators Improve the Prediction of Progression from Prediabetes to Type 2 Diabetes Mellitus.

: Diet plays an important role in preventing and managing the progression from prediabetes to type 2...

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