Diet & Nutrition

Deep learning-based identification of vertebral fracture and osteoporosis in lateral spine radiographs and DXA vertebral fracture assessment to predict incident fracture.

Deep learning (DL) identification of vertebral fractures and osteoporosis in lateral spine radiograp...

Characterizing low femoral neck BMD in Qatar Biobank participants using machine learning models.

BACKGROUND: Identifying determinants of low bone mineral density (BMD) is crucial for understanding ...

Boosting Immunity Through Nutrition and Gut Health: A Narrative Review on Managing Allergies and Multimorbidity.

The increasing global burden of allergic diseases and multimorbidity underscores the urgent need for...

Predicting overactive bladder from inflammatory markers: A machine learning approach using NHANES 2005-2020.

Overactive bladder (OAB), a prevalent condition characterized by urgency and nocturia, imposes signi...

Neonatal Nutrition Using ChatGPT.

Personalized Nutrition Strategies for Patients in the Intensive Care Unit: A Narrative Review on the Future of Critical Care Nutrition.

Critically ill patients in intensive care units (ICUs) are at high risk of malnutrition, which can ...

Artificial intelligence in cancer-related malnutrition and cachexia: a transformative tool in clinical nutrition.

Feasibility of Bone Mineral Density and Bone Microarchitecture Assessment Using Deep Learning With a Convolutional Neural Network.

OBJECTIVES: We evaluated the feasibility of using deep learning with a convolutional neural network ...

Predicting Cognitive Outcome Through Nutrition and Health Markers Using Supervised Machine Learning.

BACKGROUND: Machine learning (ML) use in health research is growing, yet its application to predict ...

Application of machine learning for the analysis of peripheral blood biomarkers in oral mucosal diseases: a cross-sectional study.

BACKGROUND: Oral mucosal lesions are widespread globally, have a high prevalence in clinical practic...

Advancing Nutritional Status Classification With Hybrid Artificial Intelligence: A Novel Methodological Approach.

PURPOSE: Malnutrition remains a critical public health issue in low-income countries, significantly ...

Impact of Tagatose on Physicochemical, Nutritional, and In Vitro Digestive Properties of Toast Bread.

It is more attractive to develop effective strategies to reduce sugar intake without compromising fo...

Explosion of formulaic research articles, including inappropriate study designs and false discoveries, based on the NHANES US national health database.

With the growth of artificial intelligence (AI)-ready datasets such as the National Health and Nutri...

Harnessing artificial intelligence for advancements in Rice / wheat functional food Research and Development.

In recent years, the research and development (R&D) of rice and wheat functional foods has attracted...

Assessing online chat-based artificial intelligence models for weight loss recommendation appropriateness and bias in the presence of guideline incongruence.

BACKGROUND AND AIM: Managing obesity requires a comprehensive approach that involves therapeutic lif...

Machine Learning in Automated Food Processing: A Mini Review.

Industrial food processing is rapidly transforming into automation and digitalization. Automated foo...

A Deep Learning Model for Three-Dimensional Determination of Whole Thoracic Vertebral Bone Mineral Density from Noncontrast Chest CT: The Multi-Ethnic Study of Atherosclerosis.

Background Recent studies have investigated how deep learning (DL) algorithms applied to CT using tw...

A Pilot Study on Using an Artificial Intelligence Algorithm to Identify Urolith Composition through Abdominal Radiographs in the Dog.

In small animal practice, patients often present with urinary lithiasis, and prediction of urolith c...

Image-based food groups and portion prediction by using deep learning.

Chronic diseases such as obesity and hypertension due to malnutrition can be prevented by following ...

Challenges for Predictive Modeling With Neural Network Techniques Using Error-Prone Dietary Intake Data.

Dietary intake data are routinely drawn upon to explore diet-health relationships, and inform clinic...

Building a cancer risk and survival prediction model based on social determinants of health combined with machine learning: A NHANES 1999 to 2018 retrospective cohort study.

The occurrence and progression of cancer is a significant focus of research worldwide, often accompa...