Latest AI and machine learning research in diet & nutrition for healthcare professionals.
Community-acquired pneumonia (CAP) is associated with high mortality, and accurate diagnosis and risk prediction are essential for improving patient outcomes. Traditional diagnostic methods have limitations, prompting the use of machine learning (ML) to enhance diagnostic precision and treatment strategies. This study aims to develop ML models to predict CAP etiology and mortality using clinical d...
INTRODUCTION: Despite the increasing number of studies using machine learning to develop individualized treatment strategies, only a few have been conducted in patients with type 1 diabetes. This study aimed to identify the characteristics of Japanese patients with type 1 diabetes, classified into subgroups using data-driven cluster analysis based on pancreatic beta-cell function, obesity, and gly...
BACKGROUND: Hypertension poses a significant public health challenge in low- and middle-income countries. In Bangladesh, the Health Population and Nut...
A healthy diet has been associated with a reduced risk of dementia. Here we devised a Machine learning-assisted Optimizing Dietary intERvention agains...
Reliable recognition of geochemical anomalies linked to ore deposits is one of the most significant challenges in mineral exploration. Several advance...
Physical inactivity is a global health issue contributing to chronic conditions like obesity and cardiovascular diseases, with regular exercise often ...
Metabolic dysfunction-associated steatohepatitis (MASH), the progressive inflammatory form of MASLD, is now a leading cause of chronic liver disease w...
BACKGROUND: Stomach adenocarcinoma (STAD) is one of most common cancers with high invasiveness and poor prognosis. Obesity and aging are correlated wi...
Precision nutrition utilizes an individualized approach in which dietary interventions are tailored according to patients' genetic, biologic, and envi...
The understanding of the molecular mechanisms that drive taste perception can have broad implications for public health. This study aims to expand the...
Cancer-associated fibroblasts promote tumor progression through growth facilitation, invasion, and immune evasion. This study investigated the impact ...
Traditional methods for measuring body composition in CT scans rely on labor-intensive manual delineation, which is time-consuming and imprecise. This...
BACKGROUND: The integration of machine learning (ML) algorithms enables the detection of diffusion abnormalities-related respiratory changes in indivi...
In recent years, global accessibility to large 'big data' repositories that enable 'open research' - such as the UK Biobank, National Health and Nutri...
The multi-elemental profile has repeatedly been proposed as a reliable indicator of the geographical origin of plant-derived foods, as mineral composi...
The worldwide prevalence of overweight and obesity has increased rapidly in the last decades. This rise has led to a surge in comorbidities such as ty...
Predicting leaf mineral composition is critical for monitoring plant health and optimizing agricultural practices. This study combines Fourier-transfo...
There are myriad factors that influence our eating habits and behaviors. Some of these factors are due to our genetic predisposition while others are ...
Multi-omics assisted prediction of disease resistance mechanisms using machine learning has the potential to accelerate the breeding of resistant legu...
Randomized controlled trials (RCTs) have demonstrated benefits of marine omega-3 polyunsaturated fatty acids (omega-3 FA) supplementation for the prev...