Diet & Nutrition

Machine learning-based simulation of groundwater DIC distribution and source apportionment.

Groundwater is an important dissolved inorganic carbon (DIC)-rich reservoir and a key link connecting atmospheric, soil, rock, and surface-water carbon pools, thereby playing an important role in regional and global carbon cycling. However, systematic understanding of DIC migration and transformation mechanisms, spatial distribution patterns, and source identification in groundwater remains limite...

Association of serum albumin redox state with dietary protein intake and frailty in older adults: A cross-sectional study.

BACKGROUND AND AIMS: Biomarkers of protein nutritional status are essential for understanding the relationship between diet and frailty. The fraction of mercaptoalbumin in total serum albumin (f(HMA)) is associated with protein deficiency and physical function in older adults. However, whether f(HMA) explains the relationship between protein intake and frailty remains unclear. We aimed to determin...

Reply to: From traditional to artificial intelligence-driven approaches: Revolutionizing personalized and precision nutrition in inflammatory bowel disease.

Homogeneity of Liver Fat Distribution Serves as a Diagnostic Marker for Metabolic Dysfunction-Associated Steatohepatitis.

RATIONALE AND OBJECTIVES: To characterize liver fat distribution in metabolic dysfunction-associated steatohepatitis (MASH) and propose a magnetic res...

Body composition's effect on the bone-vascular axis of osteoporosis discovered in AI-based CT analysis of COPD patients.

OBJECTIVES: This study aimed to investigate the effect of body composition on the inverse relationship between vertebral bone density (T12 BMD) and to...

Artificial intelligence for food innovation.

Global food systems must deliver nutritious, sustainable foods while sharply reducing environmental impact. Yet, food innovation remains slow, empiric...

Machine learning-assisted smart electrochemical platform: High-sensitivity simultaneous detection of rutin and luteolin in biological samples.

Rutin (Rn) and luteolin (Lu), as important plant-derived natural compounds, hold significant value in the fields of medicine, nutrition, and food scie...

Comment on "From traditional to artificial intelligence-driven approaches: Revolutionizing personalized and precision nutrition in inflammatory bowel disease".

Development and Validation of an Explainable Machine Learning Model to Assess the Prevalence Probability of Gastrointestinal Heat Retention Syndrome in Children: Cross-Sectional Study.

BACKGROUND: Health problems associated with energy metabolism imbalance have received increasing attention. Our team was the first to propose the conc...

Imaging-Derived Sarcopenic Obesity and Cardiovascular Outcomes: Insights Into Heart Failure Risk and Muscle Biology.

BACKGROUND: The prognostic value of obesity in cardiovascular disease is complex. Measures such as body mass index and waist-to-height ratio show diff...

Reframing Cardiometabolic Risk and Frailty Through Sarcopenic Obesity.

Construction and evaluation of a CatBoost-based machine learning model for sarcopenia prediction using bioelectrical impedance analysis (BIA) and handgrip strength (HGS) from a nationally representative dataset of Korean older adults.

This study aimed to develop and validate an explainable machine learning model for predicting sarcopenia in older adults using nationally representati...

Decoding the molecular memory of obesity using machine learning and microRNA dynamics.

Metabolomic and lifestyle profiles refine BMI-metabolic phenotypes in older adults.

Conventional BMI-based classifications, even when combined with traditional cardiometabolic risk factors, limit precision in aging-related risk assess...

BHOD: a bone health optimized dietary pattern designed for osteoporosis prevention.

Existing dietary patterns were not specifically designed to target osteoporosis and lack the precision required for effective prevention. We aimed to ...

Decision tree-based prediction of 5-year weight trajectories after bariatric surgery in adolescents and young adults: a retrospective cohort study from France and Sweden.

BACKGROUND: Metabolic-bariatric surgery is an efficient therapy in selected adolescents with severe obesity. However, predicting the postoperative wei...

Predicting the Complex, Multilevel Ecology of US County-Level Diabetes Prevalence: A Cross-Sectional, Artificial Intelligence Analysis.

BACKGROUND: Diabetes and its risk factors are embedded in a complex multilevel ecology. Upstream factors (i.e., 'forcing factors' that refer to fundam...

Using Natural Language Processing of Clinical Notes to Supplement Structured Electronic Health Record Data for Phenotyping Smoking and Obesity in a Healthcare System.

PURPOSE: Studies based on electronic health records (EHR) often rely on structured data, which may incompletely capture important clinical phenotypes ...

Polygon-Aware Deep Learning Framework for Meal-Level Nutrition Estimation From Food Images.

Accurate estimation of meal-level nutritional content from food images is a challenging yet essential task for automated dietary assessment. Although ...

An Emergency-deployable Albumin-enhanced NLR Derived by Machine Learning Improves Risk Stratification in Lung Cancer: A Multicenter Cohort Study.

BACKGROUND/AIM: Systemic inflammation is tightly linked to lung cancer prognosis, yet widely used blood-based indices show only modest discrimination....