Latest AI and machine learning research in diet & nutrition for healthcare professionals.
Nutrition estimation is an important component of promoting healthy eating and mitigating diet-related health risks. Despite advances in tasks such as food classification and ingredient recognition, progress in nutrition estimation is limited due to the lack of datasets with nutritional annotations. To address this issue, we introduce FastFood, a dataset with 84,446 images across 908 fast food c...
Metabolic syndrome (MetS) is a medication condition characterized by abdominal obesity, insulin resistance, hypertension and hyperlipidemia. It increases the risk of majority of chronic diseases, including type 2 diabetes mellitus, and affects about one quarter of the global population. Therefore, early detection and timely intervention for MetS are crucial. Standard diagnosis for MetS component...
Critically ill patients in intensive care units (ICUs) are at high risk of malnutrition, which can result in muscle atrophy, polyneuropathy, increase...
OBJECTIVES: We evaluated the feasibility of using deep learning with a convolutional neural network for predicting bone mineral density (BMD) and bone...
BACKGROUND: Machine learning (ML) use in health research is growing, yet its application to predict cognitive outcomes using diverse health indicators...
BACKGROUND: Oral mucosal lesions are widespread globally, have a high prevalence in clinical practice, and significantly impact patients' quality of l...
Rice is an essential staple food worldwide that is important in promoting international trade, economic growth, and nutrition. Asian countries such ...
Accurately tracking food consumption is crucial for nutrition and health monitoring. Traditional approaches typically require specific camera angles...
Inflammatory bowel disease (IBD), comprising ulcerative colitis and Crohn's disease, is a chronic inflammatory condition with global prevalence and va...
BACKGROUND: Metabolic syndrome (MetS) is a progressive chronic pathophysiological state characterised by abdominal obesity, hypertension, hyperglycaem...
PURPOSE: Malnutrition remains a critical public health issue in low-income countries, significantly hindering economic development and contributing to...
BACKGROUND AND AIM: Managing obesity requires a comprehensive approach that involves therapeutic lifestyle changes, medications, or metabolic surgery....
It is more attractive to develop effective strategies to reduce sugar intake without compromising food quality with the rising prevalence of obesity a...
In recent years, the research and development (R&D) of rice and wheat functional foods has attracted a widespread attention from food researchers, dri...
With the growth of artificial intelligence (AI)-ready datasets such as the National Health and Nutrition Examination Survey (NHANES), new opportunitie...
Birth weight (BW) is a key indicator of neonatal health, with low birth weight (LBW) linked to increased mortality and morbidity. Early prediction o...
A scalable and reliable system is required to analyze the National Health and Nutrition Examination Survey (NHANES) data efficiently to understand h...
Overweight and obesity have emerged as widespread societal challenges, frequently linked to unhealthy eating patterns. A promising approach to enhan...
We propose and create an incentive based recommendation algorithm aimed at improving the lifestyle of diabetic patients. This algorithm is integrate...