Oliveira, AlexandraSilva, ElianaAguiar, JoyceFaria, Brigida MonicaReis, Luís PauloCardoso, HenriqueGonçalves, JoaquimSá, Jorge Oliveira e CarvalhoVictor, Marques Herlander2020-12-042021-10-052020Oliveira, A., Silva, E., Aguiar, J., Faria, B. M., Reis, L. P., Cardoso, H., . . . Marques, H. (2020). Biometrics and quality of life of lymphoma patients: A longitudinal mixed-model approach. Expert Systems, n/a(n/a), e12640. doi:https://doi.org/10.1111/exsy.12640http://hdl.handle.net/10400.22/16524Knowledge Engineering has become essential in the fields of Medical and Health Care with emphasis for helping citizens to improve their health and quality of life. This includes individual methods and techniques in health‐related knowledge acquisition and representation and their application in the construction of intelligent systems capable of using the acquired information to improve the patients' health and/or quality of life. Haemato‐oncological diseases can provide significant disability and suffering, with severe symptoms and psychological distress. They can create difficulties in fulfilling professional, family and social roles, affecting an individual's quality of life. Health related quality of life (HRQoL) is a subjective concept but there is also an objective component related to physiological indicators. Some of these physiological indicators can be easily assessed by wearable technology such heart rate variability (HRV). This paper introduces an intelligent system to assess, in real‐time, potential HRV indices, that can predict HRQoL in lymphoma patients throughout chemotherapy treatment and to account the individuals' variability.engHaemato-oncological diseases, Wearable smart sensorsHealth-related quality of lifeHeart rate variabilityLongitudinalanalysisMixed-effect regression modelsPhysiological indicatorsjournal article10.1111/exsy.12640