Diet & Nutrition

Ingredient-Level Food Image Segmentation for Nutrition Awareness

Food images often contain several visible ingredients, so assigning one dish label to an entire image hides important visual structure. This work studies ingredient-level semantic segmentation on FoodSeg103, where the model predicts an ingredient class for each pixel. Two SegFormer variants were fine-tuned and evaluated under a controlled setup: SegFormer-B0 as the smaller baseline model and SegFo...

Cumulative Metabolic Exposure to Hyperglycemia and Risk of Cardiovascular and Limb Events in Peripheral Artery Disease

Background: Although diabetes is a potent risk factor for the development of peripheral artery disease (PAD), the effect of cumulative metabolic exposure to hyperglycemia on risk of cardiovascular or limb events in patients with PAD remains unclear. Methods: The Peripheral Artery Disease: Long-term Survival (PEARLS) is a longitudinal registry of Veterans with newly diagnosed PAD identified using a...

Comparative Analysis of Machine Learning Models vs. Traditional Clinical Calculators for Cardiovascular Risk Prediction

Background: Cardiovascular diseases (CVD) remain the leading global cause of mortality, responsible for approximately 31% of all deaths worldwide in 2...

Beyond the Blood Draw: Explainable Machine Learning for Non-Invasive Dysglycemia Risk Screening

Dysglycemia, encompassing both prediabetes and diabetes, affects huge numbers of adults worldwide, yet many of them remain undiagnosed. We developed a...

Systematic AI-Driven Drug Repurposing via Clinical Trial Data Mining: A Framework and Six Cross-Therapeutic Case Studies.

Drug repurposing, the application of approved or shelved compounds to new therapeutic indications, offers a cost- and time-efficient alternative to de...

Agreement of an AI tool for joint space width measurement in radiographic knee osteoarthritis: data from the LOSEIT trial

Background and rationale: Knee osteoarthritis (KOA) is a leading cause of lower limb disability worldwide, characterized by functional limitations, st...

Controlling metal-carbonate phase, form, and function through de novo protein design

Biomineralization enables living systems to construct hybrid materials by controlling the location, orientation, and polymorph of inorganic crystals w...

MetaPlate: Counterfactual-Guided RAG-LLM Tool for Personalized Food Recommendation and Hyperglycemia Prevention

Postprandial hyperglycemia is a key risk factor for metabolic disorders; however, existing dietary guidance is often static, impractical, and insuffic...

NutriMLLM: Multimodal Large Language Models for Dietary Micronutrient Analysis

Comprehensive estimation of dietary micronutrients from food images could improve clinical nutrition care, but training such models requires large mul...

ViTAMIn-O: Democratizing computer vision-based machine learning for stem cell research

Deep Learning (DL) holds exciting potential in automating the prediction of organoid differentiation results. Nevertheless, current models lack adapta...

Beyond the annotated: protein foundation models enable robust prediction of microbial root competence

Background Root competence, the ability of soil bacteria to establish and grow on plant roots, is a key ecological trait influencing plant nutrition, ...

Progeny differentiation in faba bean using hyperspectral images and machine learning

Though currently a minor crop, faba bean is a promising source of plant-based protein as global diets shift towards more plant-based nutrition. To rea...

Factors Influencing Vitamin D Status in Guiyang, China: A Random Forest and SHAP Analysis

Objective To assess serum 25-hydroxyvitamin D [25(OH)D] levels in a health examination population in Guiyang, a low-latitude, high-altitude, and cloud...

Overweight status drives early tumor microenvironment reprogramming in pancreatic ductal adenocarcinoma: a cell-type-resolved Bayesian hierarchical modeling and interactome analysis

Background: Obesity significantly increases the risk of prognosis and clinical outcomes in pancreatic ductal adenocarcinoma (PDAC). While research on ...

LOCOPOTS: a low-cost high-throughput screening platform for in vitro potato phenotyping under abiotic stress

Potato crop is highly vulnerable to abiotic stresses like salinity and low nutrient availability. Rapid identification of stress-resilient genotypes i...

Use of Large Language Models by U.S. Adults to Support Exercise: A Survey Study

Background: Large Language Model (LLM) chatbots are increasingly used for exercise and fitness topics, yet users' experience with these tools remains ...

Machine Learning-Assisted Feature Selection Identifies the Joint Association of Body Mass Index and Periaortic Adipose Tissue as a Risk Factor for Aortic Dissection: A Multicenter Retrospective Study

BACKGROUND: Aortic dissection (AD) is a life-threatening emergency with high mortality. Although elevated body mass index (BMI) is associated with bot...

Whom Does Algorithmic Risk Stratification Miss? A Fairness Audit of Machine Learning Targeting for Concurrent Maternal-Child Double Burden of Malnutrition Across 30 Low- and Middle-Income Countries

Author Summary In many low- and middle-income countries, mothers who are overweight often live in the same household as children who are too short or ...

Liver Biomarker Improves AHA/ACC 10-year ASCVD Risk Prediction in US and China Cohorts with ML

Introduction: Accurate stratification of hard atherosclerotic cardiovascular disease (ASCVD) risk remains challenging despite advances in prevention. ...

Opportunistic Bone-Loss Screening from Routine Knee Radiographs Using a Multi-Task Deep Learning Framework with Sensitivity-Constrained Threshold Optimization

Background: Osteoporosis and osteopenia are often undiagnosed until fragility fractures occur. Dual-energy X-ray absorptiometry (DXA) is the reference...