AIMC Topic: Nutritional Status

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Machine Learning Analysis of Nutrient Associations with Peripheral Arterial Disease: Insights from NHANES 1999-2004.

Annals of vascular surgery
BACKGROUND: Peripheral arterial disease (PAD) is a common manifestation of atherosclerosis, affecting over 200 million people worldwide. The incidence of PAD is increasing due to the aging population. Common risk factors include smoking, diabetes, an...

Prediction of stunting and its socioeconomic determinants among adolescent girls in Ethiopia using machine learning algorithms.

PloS one
BACKGROUND: Stunting is a vital indicator of chronic undernutrition that reveals a failure to reach linear growth. Investigating growth and nutrition status during adolescence, in addition to infancy and childhood is very crucial. However, the availa...

Prognosis modelling of adverse events for post-PCI treated AMI patients based on inflammation and nutrition indexes.

BMC cardiovascular disorders
OBJECTIVE: This study aimed to evaluate the predictive performance of inflammatory and nutritional indices for adverse cardiovascular events (ACE) in patients with acute myocardial infarction (AMI) after percutaneous coronary intervention (PCI) using...

Investigation and Assessment of AI's Role in Nutrition-An Updated Narrative Review of the Evidence.

Nutrients
BACKGROUND: Artificial Intelligence (AI) technologies are now essential as the agenda of nutrition research expands its scope to look at the intricate connection between food and health in both an individual and a community context. AI also helps in ...

A neural network integrated mathematical model to analyze the impact of nutritional status on cognitive development of child.

Computers in biology and medicine
Cognitive development is a crucial developmental aspect of children. It is a concise field of study in psychology and neuroscience that focuses on various developmental aspects of the brain. Among all other factors, nutritional status is believed to ...

Unlocking insights: Using machine learning to identify wasting and risk factors in Egyptian children under 5.

Nutrition (Burbank, Los Angeles County, Calif.)
INTRODUCTION: Malnutrition, particularly wasting, continues to be a significant public health issue among children under five years in Egypt. Despite global advancements in child health, the prevalence of wasting remains a critical concern. This stud...

Impact of nutrition-related laboratory tests on mortality of patients who are critically ill using artificial intelligence: A focus on trace elements, vitamins, and cholesterol.

Nutrition in clinical practice : official publication of the American Society for Parenteral and Enteral Nutrition
BACKGROUND: This study aimed to understand the collective impact of trace elements, vitamins, cholesterol, and prealbumin on patient outcomes in the intensive care unit (ICU) using an advanced artificial intelligence (AI) model for mortality predicti...

Health economic evaluation of an artificial intelligence (AI)-based rapid nutritional diagnostic system for hospitalised patients: A multicentre, randomised controlled trial.

Clinical nutrition (Edinburgh, Scotland)
BACKGROUND & AIMS: Malnutrition is prevalent among hospitalised patients, and increases the morbidity, mortality, and medical costs; yet nutritional assessments on admission are not routine. This study assessed the clinical and economic benefits of u...

[Medicine of the future: the role of artificial intelligence in optimizing nutrition for the health of the Russian population].

Voprosy pitaniia
One of the most pressing medical, social and government tasks is to ensure health saving, improve the quality of life and increase the life expectancy of the Russian population. The most important lever to ensure the solution of these issues is the o...