All Outputs (3)

The measurement of dietary species richness reveals that a higher consumption of dietary fibre, fish, fruits and vegetables, is associated with greater food biodiversity in UK diets. (2025)
Journal Article
ACEVES-MARTINS, M., LÖFSTEDT, A., MORENO-GARCÍA, C.F., ZANDSTRA, E.H., WANDERS, A.J. and DE ROOS, B. 2025. The measurement of dietary species richness reveals that a higher consumption of dietary fibre, fish, fruits and vegetables, is associated with greater food biodiversity in UK diets. Public health nutrition [online], Accepted manuscript. Available from: https://doi.org/10.1017/s1368980025000473

We determined whether Dietary Species Richness (DSR) i) can be robustly measured using four-day food intake data, ii) is dependent on sociodemographic characteristics, and iii) is associated with diet quality. The National Diet and Nutrition Survey (... Read More about The measurement of dietary species richness reveals that a higher consumption of dietary fibre, fish, fruits and vegetables, is associated with greater food biodiversity in UK diets..

Socioeconomic determinants of overweight and obesity among Mexican children and adolescents: systematic review and meta‐analysis (2025)
Journal Article
ACEVES-MARTINS, M., GUTIERREZ-GÓMEZ, Y.Y. and MORENO-GARCÍA, C.F. 2025. Socioeconomic determinants of overweight and obesity among Mexican children and adolescents: systematic review and meta-analysis. Obesity reviews [online], Early View, article number e13926. Available from: https://doi.org/10.1111/obr.13926

Socioeconomic status (SES) has widely been studied as a potential risk factor for obesity among children and adolescents. Nevertheless, SES determinants are rarely contextualized within a country's situation. This work aimed to identify SES factors a... Read More about Socioeconomic determinants of overweight and obesity among Mexican children and adolescents: systematic review and meta‐analysis.

Understanding disagreement between humans and machines in XAI: robustness, fidelity, and region-based explanations in automatic neonatal pain assessment. (2025)
Presentation / Conference Contribution
PIRIE, C., FERREIRA, L.A., COUTRIN, G.A.S., CARLINI, L.P., MORENO-GARCÍA, C.F., BARROS, M.C.M., GUINSBURG, R., THOMAZ, C.E., NOBRE, R. and WIRATUNGA, N. Understanding disagreement between humans and machines in XAI: robustness, fidelity, and region-based explanations in automatic neonatal pain assessment. [2025]. To be presented at the 3rd World conference on eXplainable artificial intelligence 2025, 9-11 July 2025, Istanbul, Turkey.

Artificial Intelligence (AI) offers a promising approach to automating neonatal pain assessment, improving consistency and objectivity in clinical decision-making. However, differences between how humans and AI models perceive and explain pain-relate... Read More about Understanding disagreement between humans and machines in XAI: robustness, fidelity, and region-based explanations in automatic neonatal pain assessment..