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Meals

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Appetite ratings of foods are predictable with an in vitro advanced gastrointestinal model in combination with an in silico artificial neural network.

Food research international (Ottawa, Ont.)
The expected increase of global obesity prevalence makes it necessary to have information about the effects of meal intakes on the feeling of appetite. Because human clinical studies are time and cost intensive, there is a need for a reliable alterna...

Assessment of In-Meal Eating Behaviour using Fuzzy SVM.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Certain patterns of eating behaviour during meal have been identified as risk factors for long-term abnormal eating development in healthy individuals and, eventually, can affect the body weight. To detect early signs of problematic eating behaviour,...

An Artificial Intelligence-Based System for Nutrient Intake Assessment of Hospitalised Patients.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Regular nutrient intake monitoring in hospitalised patients plays a critical role in reducing the risk of disease-related malnutrition (DRM). Although several methods to estimate nutrient intake have been developed, there is still a clear demand for ...

Detecting Meals In the Wild Using the Inertial Data of a Typical Smartwatch.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Automated and objective monitoring of eating behavior has received the attention of both the research community and the industry over the past few years. In this paper we present a method for automatically detecting meals in free living conditions, u...

Validation of a Deep Learning System for the Full Automation of Bite and Meal Duration Analysis of Experimental Meal Videos.

Nutrients
Eating behavior can have an important effect on, and be correlated with, obesity and eating disorders. Eating behavior is usually estimated through self-reporting measures, despite their limitations in reliability, based on ease of collection and ana...

Glucose outcomes of a learning-type artificial pancreas with an unannounced meal in type 1 diabetes.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Glycemic control with unannounced meals is the major challenge for artificial pancreas. In this study, we described the performance and safety of learning-type model predictive control (L-MPC) for artificial pancreas challe...

goFOOD: An Artificial Intelligence System for Dietary Assessment.

Sensors (Basel, Switzerland)
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...

A Universal Approximation Result for Difference of Log-Sum-Exp Neural Networks.

IEEE transactions on neural networks and learning systems
We show that a neural network whose output is obtained as the difference of the outputs of two feedforward networks with exponential activation function in the hidden layer and logarithmic activation function in the output node, referred to as log-su...

Evaluation of a Novel Artificial Intelligence System to Monitor and Assess Energy and Macronutrient Intake in Hospitalised Older Patients.

Nutrients
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...

Automated food intake tracking requires depth-refined semantic segmentation to rectify visual-volume discordance in long-term care homes.

Scientific reports
Malnutrition is a multidomain problem affecting 54% of older adults in long-term care (LTC). Monitoring nutritional intake in LTC is laborious and subjective, limiting clinical inference capabilities. Recent advances in automatic image-based food est...