Research Articles
Beyond One-Size-Fits-All: Decoding Inter-Individual Variability in Nutritional Responses for Precision Health
This article provides a comprehensive analysis of inter-individual variability in responses to nutritional interventions, a critical factor often overlooked in traditional diet-related research and drug development.
Overcoming Methodological Challenges in Food Nutrient Analysis: From Data Gaps to AI Solutions
This article addresses the complex methodological challenges in food nutrient analysis, a critical field for researchers, scientists, and drug development professionals.
Local vs. Global Food Supply Chains: A Scientific Framework for Nutritional Quality Assessment in Biomedical Contexts
This article provides researchers, scientists, and drug development professionals with a comprehensive analytical framework for assessing the nutritional quality of foods from local and global supply chains.
Beyond the Single Nutrient: Navigating Methodological Limitations in Dietary Patterns Synthesis for Robust Biomedical Research
This article addresses the critical methodological challenges and limitations that researchers face when synthesizing evidence on dietary patterns.
Beyond Traditional Methods: Leveraging Latent Class Analysis for Advanced Dietary Pattern Discovery in Biomedical Research
This article explores the application of Latent Class Analysis (LCA) as a novel, person-centered statistical method for identifying complex dietary patterns in population studies.
Advancing Wristband Nutrition Tracking: Accuracy Challenges and AI-Driven Solutions for Biomedical Research
This article provides a comprehensive analysis for researchers and drug development professionals on the current state, challenges, and emerging solutions in wristband-based nutrition tracking.
From Lab to Life: Evaluating Wearable Eating Detection Performance in Controlled vs. Free-Living Environments
This article provides a comprehensive analysis for researchers and drug development professionals on the performance of wearable sensors for automatic eating detection, contrasting controlled laboratory settings with free-living conditions.
Machine Learning for Eating Behavior Classification: Advanced Algorithms, Applications, and Clinical Translation
This article provides a comprehensive exploration of machine learning (ML) applications for classifying and predicting eating behaviors.
Beyond the Calorie Count: Assessing Wearable Sensor Technologies for Dietary Intake Monitoring in Clinical Research
This article provides a comprehensive analysis of wearable device technologies for caloric and dietary intake assessment, tailored for researchers and drug development professionals.
Beyond Self-Report: A Researcher's Guide to Objective Food Intake Measurement
Accurate measurement of food intake is critical for advancing nutritional science, validating therapeutic efficacy, and understanding diet-disease relationships.