Towards an Evaluation Framework for Explainable Artificial Intelligence Systems for Health and Well-Being

Esperança Amengual-Alcover, Antoni Jaume-i-Capó, Miquel Miró-Nicolau, Gabriel Moyà-Alcover, Antonia Paniza-Fullana

2025

Abstract

The integration of Artificial Intelligence in the development of computer systems presents a new challenge: make intelligent systems explainable to humans. This is especially vital in the field of health and well-being, where transparency in decision support systems enables healthcare professionals to understand and trust automated decisions and predictions. To address this need, tools are required to guide the development of explainable AI systems. In this paper, we introduce an evaluation framework designed to support the development of explainable AI systems for health and well-being. Additionally, we present a case study that illustrates the application of the framework in practice. We believe that our framework can serve as a valuable tool not only for developing explainable AI systems in healthcare but also for any AI system that has a significant impact on individuals.

Paper Citation

in Harvard Style

Amengual-Alcover E., Jaume-i-Capó A., Miró-Nicolau M., Moyà-Alcover G. and Paniza-Fullana A. (2025). Towards an Evaluation Framework for Explainable Artificial Intelligence Systems for Health and Well-Being. In Proceedings of the 20th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE; ISBN 978-989-758-742-9, SciTePress, pages 530-540. DOI: 10.5220/0013289600003928

in Bibtex Style

@conference{enase25,
author={Esperança Amengual-Alcover and Antoni Jaume-i-Capó and Miquel Miró-Nicolau and Gabriel Moyà-Alcover and Antonia Paniza-Fullana},
title={Towards an Evaluation Framework for Explainable Artificial Intelligence Systems for Health and Well-Being},
booktitle={Proceedings of the 20th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE},
year={2025},
pages={530-540},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013289600003928},
isbn={978-989-758-742-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE
TI - Towards an Evaluation Framework for Explainable Artificial Intelligence Systems for Health and Well-Being
SN - 978-989-758-742-9
AU - Amengual-Alcover E.
AU - Jaume-i-Capó A.
AU - Miró-Nicolau M.
AU - Moyà-Alcover G.
AU - Paniza-Fullana A.
PY - 2025
SP - 530
EP - 540
DO - 10.5220/0013289600003928
PB - SciTePress