Prevention

Image-based food groups and portion prediction by using deep learning.

Chronic diseases such as obesity and hypertension due to malnutrition can be prevented by following the appropriate diet, correct diet intake with correct measuring portion size, and developing healthy eating habits. Having a system that can automatically measure food consumption is important to determine whether individual nutritional needs are being met in order to accurately diagnose and solve ...

NutriGen: Personalized Meal Plan Generator Leveraging Large Language Models to Enhance Dietary and Nutritional Adherence

Maintaining a balanced diet is essential for overall health, yet many individuals struggle with meal planning due to nutritional complexity, time constraints, and lack of dietary knowledge. Personalized food recommendations can help address these challenges by tailoring meal plans to individual preferences, habits, and dietary restrictions. However, existing dietary recommendation systems often ...

Challenges for Predictive Modeling With Neural Network Techniques Using Error-Prone Dietary Intake Data.

Dietary intake data are routinely drawn upon to explore diet-health relationships, and inform clinical practice and public health. However, these data...

PyEvalAI: AI-assisted evaluation of Jupyter Notebooks for immediate personalized feedback

Grading student assignments in STEM courses is a laborious and repetitive task for tutors, often requiring a week to assess an entire class. For stu...

MultiFlow: A unified deep learning framework for multi-vessel classification, segmentation and clustering of phase-contrast MRI validated on a multi-site single ventricle patient cohort

This study presents a unified deep learning (DL) framework, MultiFlowSeg, for classification and segmentation of velocity-encoded phase-contrast mag...

AAKT: Enhancing Knowledge Tracing with Alternate Autoregressive Modeling

Knowledge Tracing (KT) aims to predict students' future performances based on their former exercises and additional information in educational setti...

Illegal Waste Detection in Remote Sensing Images: A Case Study

Environmental crime is the third largest criminal activity worldwide, with significant revenues coming from illegal management of solid waste. Thank...

DE-PADA: Personalized Augmentation and Domain Adaptation for ECG Biometrics Across Physiological States

Electrocardiogram (ECG)-based biometrics offer a promising method for user identification, combining intrinsic liveness detection with morphological...

Limitations of Large Language Models in Clinical Problem-Solving Arising from Inflexible Reasoning

Large Language Models (LLMs) have attained human-level accuracy on medical question-answer (QA) benchmarks. However, their limitations in navigating...

Concept-Aware Latent and Explicit Knowledge Integration for Enhanced Cognitive Diagnosis

Cognitive diagnosis can infer the students' mastery of specific knowledge concepts based on historical response logs. However, the existing cognitiv...

IRONMAP: Iron Network Mapping and Analysis Protocol for Detecting Over-Time Brain Iron Abnormalities in Neurological Disease

Pathologically altered iron levels, detected using iron-sensitive MRI techniques such as quantitative susceptibility mapping (QSM), are observed in ...

Leveraging Large Language Models to Enhance Machine Learning Interpretability and Predictive Performance: A Case Study on Emergency Department Returns for Mental Health Patients

Importance: Emergency department (ED) returns for mental health conditions pose a major healthcare burden, with 24-27% of patients returning within ...

Agent4Edu: Generating Learner Response Data by Generative Agents for Intelligent Education Systems

Personalized learning represents a promising educational strategy within intelligent educational systems, aiming to enhance learners' practice effic...

Adaptive Experiments Under High-Dimensional and Data Sparse Settings: Applications for Educational Platforms

In online educational platforms, adaptive experiment designs play a critical role in personalizing learning pathways, instructional sequencing, and ...

From Occasional to Steady: Habit Formation Insights From a Comprehensive Fitness Study

Exercising regularly is widely recognized as a cornerstone of health, yet the challenge of sustaining consistent exercise habits persists. Understan...

Matrix effects influence biochemical signatures and metabolite quantification in dried blood spots

Dried blood spots (DBS) represent a convenient clinical sample material, offering low infection risk, easy transport, and long-term metabolite stabili...

Integrative Analysis of the Mouse Cecal Microbiome Across Diet, Age, and Metabolic State in the Diverse BXD Population

The gut microbiota both adapts to, and shapes, the host’s metabolic state through metabolites and gene regulatory networks, influencing multiple organ...

Bat anthropogenic roosting ecology influences taxonomic and geographic predictions of zoonotic risk

The ability of wildlife to live in anthropogenic structures is widely observed across many animal species. As proximity to humans is an important risk...

Dietary Protein Source Shapes Gut Microbial Structure and Predicted Function: A Meta-Analysis with Machine Learning

Dietary proteins are major modulators of gut microbial ecology, yet the microbial signatures and functional consequences of plant-versus animal-based ...

A Transparent and Generalizable Deep Learning Framework for Genomic Ancestry Prediction

Accurately capturing genetic ancestry is critical for ensuring reproducibility and fairness in genomic studies and downstream health research. This st...