Diet & Nutrition

Fuzzy Cognitive Maps with Bird Swarm Intelligence Optimization-Based Remote Sensing Image Classification.

Remote sensing image (RSI) scene classification has become a hot research topic due to its applicability in different domains such as object recognition, land use classification, image retrieval, and surveillance. During RSI classification process, a class label will be allocated to every scene class based on the semantic details, which is significant in real-time applications such as mineral expl...

A deep learning-based approach to automatic proximal femur segmentation in quantitative CT images.

Automatic CT segmentation of proximal femur has a great potential for use in orthopedic diseases, especially in the imaging-based assessments of hip fracture risk. In this study, we proposed an approach based on deep learning for the fast and automatic extraction of the periosteal and endosteal contours of proximal femur in order to differentiate cortical and trabecular bone compartments. A three-...

Pre-germinated brown rice alleviates non-alcoholic fatty liver disease induced by high fructose and high fat intake in rat.

In past researches, we had been proved the action mechanism of pre-germinated brown rice (PGBR) to treat metabolic syndrome and diabetes mellitus. Thi...

Responsible Governance for a Food and Nutrition E-Infrastructure: Case Study of the Determinants and Intake Data Platform.

The focus of the current paper is on a design of responsible governance of food consumer science e-infrastructure using the case study Determinants an...

Development of CNN models for the enteral feeding tube positioning assessment on a small scale data set.

BACKGROUND: Enteral nutrition through feeding tubes serves as the primary method of nutritional supplementation for patients unable to feed themselves...

Impact of the training loss in deep learning-based CT reconstruction of bone microarchitecture.

PURPOSE: Computed tomography (CT) is a technique of choice to image bone structure at different scales. Methods to enhance the quality of degraded rec...

Intelligent Localization Sampling System Based on Deep Learning and Image Processing Technology.

In this paper, deep learning and image processing technologies are combined, and an automatic sampling robot is proposed that can completely replace t...

Research on Classification of Open-Pit Mineral Exploiting Information Based on OOB RFE Feature Optimization.

Mineral exploiting information is an important indicator to reflect regional mineral activities. Accurate extraction of this information is essential ...

Estimation and Prediction of Hospitalization and Medical Care Costs Using Regression in Machine Learning.

Medical costs are one of the most common recurring expenses in a person's life. Based on different research studies, BMI, ageing, smoking, and other f...

Body fat prediction through feature extraction based on anthropometric and laboratory measurements.

Obesity, associated with having excess body fat, is a critical public health problem that can cause serious diseases. Although a range of techniques f...

Evolution of hospitalized patient characteristics through the first three COVID-19 waves in Paris area using machine learning analysis.

Characteristics of patients at risk of developing severe forms of COVID-19 disease have been widely described, but very few studies describe their evo...

A Novel Method of Multitype Hybrid Rock Lithology Classification Based on Convolutional Neural Networks.

Rock lithology recognition plays a fundamental role in geological survey research, mineral resource exploration, mining engineering, etc. However, the...

Associations Between Different Dietary Vitamins and the Risk of Obesity in Children and Adolescents: A Machine Learning Approach.

BACKGROUNDS: Simultaneous dietary intake of vitamins is considered as a common and real scenario in daily life. However, limited prospective studies h...

Evaluating the robustness of targeted maximum likelihood estimators via realistic simulations in nutrition intervention trials.

Several recently developed methods have the potential to harness machine learning in the pursuit of target quantities inspired by causal inference, in...

Machine learning-based diagnosis and risk factor analysis of cardiocerebrovascular disease based on KNHANES.

The prevalence of cardiocerebrovascular disease (CVD) is continuously increasing, and it is the leading cause of human death. Since it is difficult fo...

Classification of Citrus Diseases Using Optimization Deep Learning Approach.

Most plant diseases have apparent signs, and today's recognized method is for an expert plant pathologist to identify the disease by looking at infect...

Joint Communication and Sensing: A Proof of Concept and Datasets for Greenhouse Monitoring Using LoRaWAN.

In recent years, greenhouse-based precision agriculture (PA) has been strengthened by utilization of Internet of Things applications and low-power wid...

An explainable machine learning-based clinical decision support system for prediction of gestational diabetes mellitus.

Gestational Diabetes Mellitus (GDM), a common pregnancy complication associated with many maternal and neonatal consequences, is increased in mothers ...

The Anti-Adiposity Mechanisms of Ampelopsin and Vine Tea Extract in High Fat Diet and Alcohol-Induced Fatty Liver Mouse Models.

(AG) is an ancient medicinal plant that is mainly distributed and used in southwest China. It exerts therapeutic effects, such as antioxidant, anti-d...

Application of a Machine Learning Technology in the Definition of Metabolically Healthy and Unhealthy Status: A Retrospective Study of 2567 Subjects Suffering from Obesity with or without Metabolic Syndrome.

The key factors playing a role in the pathogenesis of metabolic alterations observed in many patients with obesity have not been fully characterized. ...