Primary Care

Diet & Nutrition

Latest AI and machine learning research in diet & nutrition for healthcare professionals.

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The effect of consuming different proportions of hummer fish on biochemical and histopathological changes of hyperglycemic rats.

Hammour fish (grouper fish) are known to be of great nutritional value for human consumption, as the...

Exploring domains, clinical implications and environmental associations of a deep learning marker of biological ageing.

Deep Neural Networks (DNN) have been recently developed for the estimation of Biological Age (BA), t...

Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis.

The fracture risk of patients with diabetes is higher than those of patients without diabetes due to...

Towards personalized nutritional treatment for malnutrition using machine learning-based screening tools.

Early identification of patients at risk of malnutrition or who are malnourished is crucial in order...

Effect of Patient Clinical Variables in Osteoporosis Classification Using Hip X-rays in Deep Learning Analysis.

: A few deep learning studies have reported that combining image features with patient variables enh...

Prediction Models of Early Childhood Caries Based on Machine Learning Algorithms.

In this study, we developed machine learning-based prediction models for early childhood caries and ...

A novel method based on machine vision system and deep learning to detect fraud in turmeric powder.

Assessing the quality of food and spices is particularly important in ensuring proper human nutritio...

Development and validation of a new diabetes index for the risk classification of present and new-onset diabetes: multicohort study.

In this study, we aimed to propose a novel diabetes index for the risk classification based on machi...

CAFT: a deep learning-based comprehensive abdominal fat analysis tool for large cohort studies.

BACKGROUND: There is increasing appreciation of the association of obesity beyond co-morbidities, su...

Development of an artificial neural network as a tool for predicting the chemical attributes of fresh peach fruits.

This investigation aimed to develop a method to predict the total soluble solids (TSS), titratable a...

Applicability of machine learning techniques in food intake assessment: A systematic review.

The evaluation of food intake is important in scientific research and clinical practice to understan...

Data-driven identification of complex disease phenotypes.

Disease interaction in multimorbid patients is relevant to treatment and prognosis, yet poorly under...

Transmol: repurposing a language model for molecular generation.

Recent advances in convolutional neural networks have inspired the application of deep learning to o...

Prophylactic effect of . seed extract on inflammatory markers and histopathological changes in high-fat-fed ovariectomized rats.

BACKGROUND AND AIM: L. seeds (TFG) are used as spices in Indian cuisine. In Indian traditional medi...

Biological Age Prediction From Wearable Device Movement Data Identifies Nutritional and Pharmacological Interventions for Healthy Aging.

Intervening in aging processes is hypothesized to extend healthy years of life and treat age-related...

Machine Learning to Identify Metabolic Subtypes of Obesity: A Multi-Center Study.

BACKGROUND AND OBJECTIVE: Clinical characteristics of obesity are heterogenous, but current classifi...

A Robust Context-Based Deep Learning Approach for Highly Imbalanced Hyperspectral Classification.

Hyperspectral imaging is an area of active research with many applications in remote sensing, minera...

Bone mineral density response prediction following osteoporosis treatment using machine learning to aid personalized therapy.

Osteoporosis is a global health problem for ageing populations. The goals of osteoporosis treatment ...

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