RT Journal Article
T1 Population-based detection of children ASD/ADHD comorbidity from atypical sensory processing
A1 Fernández Delgado, Manuel
A1 Cruz, Sara
A1 Cernadas García, Eva
A1 Alateyat, Heba
A1 Tubío-Fungueiriño, María
A1 Sampaio, Adriana
A1 Carracedo Álvarez, Ángel
A1 Fernández-Prieto, Montse
K1 Machine learning
K1 Classification
K1 ASD
K1 ADHD
K1 Sensory profile
K1 Feature selection
K1 Unbalanced classification
AB Comorbidity between neurodevelopmental disorders is common, especially between autism spectrum disorder (ASD) and attention deficit/hyperactivity disorder (ADHD). This study aimed to detect overlapped sensory processing alterations in a sample of children and adolescents diagnosed with both ASD and ADHD. A collection of 42 standard and 8 proposed machine learning classifiers, 22 feature selection methods and 19 unbalanced classification strategies were applied on the 6 standard question groups of the Sensory Profile-2 questionnaire. The relatively low performance achieved by state-of-the-art classifiers led us to propose the feature population sum classifier, a probabilistic method based on class and feature value populations, designed for datasets where features are discrete numeric answers to questions in a questionnaire. The proposed method achieves the best kappa and accuracy, 60% and 82.5%, respectively, reaching 68% and 86.5% combined with backward sequential feature selection, with false positive and negative rates below 15%. Since the SP2 questionnaire can be filled by parents for children from three years, our prediction can alert the clinicians with an early diagnosis in order to apply early interventions.
PB Springer
SN 0924-669X
YR 2024
FD 2024-07-29
LK https://hdl.handle.net/10347/39825
UL https://hdl.handle.net/10347/39825
LA eng
NO Fernández-Delgado, M., Cruz, S., Cernadas, E. et al. Population-based detection of children ASD/ADHD comorbidity from atypical sensory processing. Appl Intell 54, 9906–9923 (2024). https://doi.org/10.1007/s10489-024-05655-z
NO This work has received financial support from the Consellería de Educación, Universidade e Formación Profesional (accreditation 2019-2022 ED431G-2019/04) and the European Regional Development Fund (ERDF), which acknowledges the CiTIUS (Centro Singular de Investigación en Tecnoloxías Intelixentes da Universidade de Santiago de Compostela) as a Research Center of the Galician University System. Sara Cruz is supported by the Psychology for Development Research Center, Lusíada University, Portugal, supported by FCT - Fundação para a Ciência e Tecnologia, I.P., by project reference UIDB/04375/2020 and DOI identifier <10.54499/UIDB/04375/2020 (https://doi.org/10.54499/UIBD/04375/2020)>. Adriana Sampaio is supported by the Psychology Research Center (PSI/01662), School of Psychology, University of Minho, through the Foundation for Science and Technology (FCT) and the Portuguese State Budget (Ref. UIDB/PSI/01662/2020). María Tubío-Fungueiriño, Angel Carracedo, and Montse Fernández-Prieto were funded by Instituto de Salud Carlos III (projects PI19/00809 and PI22/00208 to Angel Carracedo) and co-funded by European Union (ERDF) “A way of making Europe”, and by Fundación María José Jove.
DS Minerva
RD 24 abr 2026