Diet & Nutrition

Artificial Intelligence Technology for Food Nutrition.

Food nutrition is generally defined as the heat energy and nutrients obtained from food by the human...

Correlation between serum 25(OH)D levels with severity of work-related hand eczema among healthcare workers: a cross-sectional study.

Hand eczema (HE) is a common condition seen in medical facilities, particularly during the COVID-19 ...

Automated vertebral bone mineral density measurement with phantomless internal calibration in chest LDCT scans using deep learning.

OBJECTIVE: To develop and evaluate a fully automated method based on deep learning and phantomless i...

Taylor Remora optimization enabled deep learning algorithms for percentage of pesticide detection in grapes.

In the world, grapes are considered as the most significant fruit, and it comprises various nutrient...

Correlation between 25-hydroxy-vitamin D and Parkinson's disease.

BACKGROUND: Previous cross-sectional studies have shown that Parkinson's disease (PD) patients have ...

Machine learning and personalized nutrition: a promising liaison?

Potential interaction of sugar intake and tobacco exposure on dental caries in adults-A cross-sectional study from the National Health and Nutrition Examination Survey.

BACKGROUND/PURPOSE: We suspected that there might be an interaction between sugar intake and tobacco...

Sentiment Analysis of Tweets on Menu Labeling Regulations in the US.

Menu labeling regulations in the United States mandate chain restaurants to display calorie informat...

An interpretable machine learning model of cross-sectional U.S. county-level obesity prevalence using explainable artificial intelligence.

BACKGROUND: There is considerable geographic heterogeneity in obesity prevalence across counties in ...

Establish and validate the reliability of predictive models in bone mineral density by deep learning as examination tool for women.

UNLABELLED: While FRAX with BMD could be more precise in estimating the fracture risk, DL-based mode...

Combining Deep Learning and Radiomics for Automated, Objective, Comprehensive Bone Mineral Density Assessment From Low-Dose Chest Computed Tomography.

RATIONALE AND OBJECTIVES: To develop an intelligent diagnostic model for osteoporosis screening base...

Comparison between linear regression and four different machine learning methods in selecting risk factors for osteoporosis in a Chinese female aged cohort.

BACKGROUND: Population aging is emerging as an increasingly acute challenge for countries around the...

Evaluation of calcium ion release from apical plugs formed by Biodentine and MTA with and without incorporation of triple antibiotic powder and modified triple antibiotic powder (cefaclor) using atomic absorption spectrophotometry - An study.

INTRODUCTION: Apexification procedure with Mineral trioxide aggregate (MTA) and Biodentine as apical...

EXIST: EXamining rIsk of excesS adiposiTy-Machine learning to predict obesity-related complications.

BACKGROUND: Obesity is associated with an increased risk of multiple conditions, ranging from heart ...

Mitigating underreported error in food frequency questionnaire data using a supervised machine learning method and error adjustment algorithm.

BACKGROUND: Food frequency questionnaires (FFQs) are one of the most useful tools for studying and u...

The Nutritional Content of Meal Images in Free-Living Conditions-Automatic Assessment with goFOOD.

A healthy diet can help to prevent or manage many important conditions and diseases, particularly ob...

Protocol of a parallel, randomized controlled trial on the effects of a novel personalized nutrition approach by artificial intelligence in real world scenario.

BACKGROUND: Nutrition service needs are huge in China. Previous studies indicated that personalized ...

The future of artificial intelligence in clinical nutrition.

PURPOSE OF REVIEW: Artificial intelligence has reached the clinical nutrition field. To perform pers...

Multimodal deep learning as a next challenge in nutrition research: tailoring fermented dairy products based on -mediated lipid metabolism.

Deep learning is evolving in nutritional epidemiology to address challenges including precise nutrit...

An unsupervised wavelet neural network model for approximating the solutions of non-linear nervous stomach model governed by tension, food and medicine.

The human stomach is a complex organ. Its role is to degrade food particles by using mechanical forc...

Adolescent relational behaviour and the obesity pandemic: A descriptive study applying social network analysis and machine learning techniques.

AIM: To study the existence of subgroups by exploring the similarities between the attributes of the...