AIMC Topic: Nutrition Assessment
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Evaluation of a Novel Artificial Intelligence System to Monitor and Assess Energy and Macronutrient Intake in Hospitalised Older Patients.
Nutrients
Dec 17, 2021
Malnutrition is common, especially among older, hospitalised patients, and is associated with higher mortality, longer hospitalisation stays, infections, and loss of muscle mass. It is therefore of utmost importance to employ a proper method for diet...
Artificial Neural Network Algorithms to Predict Resting Energy Expenditure in Critically Ill Children.
Nutrients
Oct 26, 2021
INTRODUCTION: Accurate assessment of resting energy expenditure (REE) can guide optimal nutritional prescription in critically ill children. Indirect calorimetry (IC) is the gold standard for REE measurement, but its use is limited. Alternatively, RE...
Deep neural network for automatic volumetric segmentation of whole-body CT images for body composition assessment.
Clinical nutrition (Edinburgh, Scotland)
Jul 15, 2021
BACKGROUND & AIMS: Body composition analysis on CT images is a valuable tool for sarcopenia assessment. We aimed to develop and validate a deep neural network applicable to whole-body CT images of PET-CT scan for the automatic volumetric segmentation...
Body Composition
Radiopharmaceuticals
Fluorodeoxyglucose F18
Intra-Abdominal Fat
Subcutaneous Fat
Whole Body Imaging
Abdomen
Sarcopenia
Muscle, Skeletal
Positron Emission Tomography Computed Tomography
Aged
Male
Middle Aged
Nutrition Assessment
Humans
Neural Networks, Computer
Retrospective Studies
Republic of Korea
Female
A fusion decision system to identify and grade malnutrition in cancer patients: Machine learning reveals feasible workflow from representative real-world data.
Clinical nutrition (Edinburgh, Scotland)
Jul 3, 2021
BACKGROUND AND AIMS: Most nutritional assessment tools are based on pre-defined questionnaires or consensus guidelines. However, it has been postulated that population data can be used directly to develop a solution for assessing malnutrition. This s...
Deep Neural Networks for Image-Based Dietary Assessment.
Journal of visualized experiments : JoVE
Mar 13, 2021
Due to the issues and costs associated with manual dietary assessment approaches, automated solutions are required to ease and speed up the work and increase its quality. Today, automated solutions are able to record a person's dietary intake in a mu...
Optimising an FFQ Using a Machine Learning Pipeline to teach an Efficient Nutrient Intake Predictive Model.
Nutrients
Dec 10, 2020
Food frequency questionnaires (FFQs) are the most commonly selected tools in nutrition monitoring, as they are inexpensive, easily implemented and provide useful information regarding dietary intake. They are usually carefully drafted by experts from...
goFOOD: An Artificial Intelligence System for Dietary Assessment.
Sensors (Basel, Switzerland)
Jul 31, 2020
Accurate estimation of nutritional information may lead to healthier diets and better clinical outcomes. We propose a dietary assessment system based on artificial intelligence (AI), named goFOOD. The system can estimate the calorie and macronutrient...
Current Developments in Digital Quantitative Volume Estimation for the Optimisation of Dietary Assessment.
Nutrients
Apr 22, 2020
Obesity is a global health problem with wide-reaching economic and social implications. Nutrition surveillance systems are essential to understanding and addressing poor dietary practices. However, diets are incredibly diverse across populations and ...
Food Liking-Based Diet Quality Indexes (DQI) Generated by Conceptual and Machine Learning Explained Variability in Cardiometabolic Risk Factors in Young Adults.
Nutrients
Mar 25, 2020
The overall pattern of a diet (diet quality) is recognized as more important to health and chronic disease risk than single foods or food groups. Indexes of diet quality can be derived theoretically from evidence-based recommendations, empirically fr...
Potential Confounders in the Analysis of Brazilian Adolescent's Health: A Combination of Machine Learning and Graph Theory.
International journal of environmental research and public health
Dec 21, 2019
The prevalence of health problems during childhood and adolescence is high in developing countries such as Brazil. Social inequality, violence, and malnutrition have strong impact on youth health. To better understand these issues we propose to combi...
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