- Visiestuk Towards digital life: een toekomstvisie op AI anno 2032 [Vision paper Towards digital life: a vision of AI in 2032]
- HDHL-INTIMIC: A European Knowledge Platform on Food, Diet, Intestinal Microbiomics, and Human Health
- Assessment of Oxidative Stress and Metabolic Risks With Machine Learning Algorithms in Ethnically Diverse Population: Cross-Sectional Data in Korea and the Netherlands
- Dietary Macronutrient Composition in Relation to Circulating HDL and Non-HDL Cholesterol: A Federated Individual-Level Analysis of Cross-Sectional Data from Adolescents and Adults in 8 European Studies
- Identification and Characterization of Human Observational Studies in Nutritional Epidemiology on Gut Microbiomics for Joint Data Analysis
- A Machine Learning Algorithm for Quantitatively Diagnosing Oxidative Stress Risks in Healthy Adult Individuals Based on Health Space Methodology: A Proof-of-Concept Study Using Korean Cross-Sectional Cohort Data
- A Proof-of-Concept System Dynamics Simulation Model of the Development of Burnout and Recovery Using Retrospective Case Data
- OBEDIS Core Variables Project: European Expert Guidelines on a Minimal Core Set of Variables to Include in Randomized, Controlled Clinical Trials of Obesity Interventions
- An Ontology to Standardize Research Output of Nutritional Epidemiology: From Paper-Based Standards to Linked Content