Search Publication
Biological brain age prediction using machine learning on structural neuroimaging data: Multi-cohort validation against biomarkers of Alzheimer’s disease and neurodegeneration stratified by sex. In 15th Clinical Trials on Alzheimer’s Disease Conference (CTAD). San Francisco, USA; 2022.
. Biological Brain Age Prediction Using Machine Learning on Structural Neuroimaging Data: Multi-Cohort Validation Against Biomarkers of Alzheimer’s Disease and Neurodegeneration. In Alzheimer's Association International Conference. 2022.
. BIOLOGICAL BRAIN-AGE PREDICTION USING MACHINE LEARNING ON NEUROIMAGING DATA: LINKS WITH PATHOPHYSIOLOGICAL MECHANISMS, DEMENTIA RISK FACTORS AND COGNITIVE DECLINE. Department of Experimental and Health Sciences (DCEXS), Universitat Pompeu Fabra. 2024.
. Brain structural alterations in cognitively unimpaired individuals with discordant amyloid-β PET and CSF Aβ42 status: findings using Machine Learning. In Alzheimer's Association International Conference. 2021.
. Brain-age mediates the association between modifiable risk factors and cognitive decline early in the AD continuum. In Alzheimer’s Association International Conference (AAIC). Amsterdam, Netherlands; 2023.
. Brain-age prediction and its associations with glial and synaptic CSF markers. In Alzheimer's Association International Conference. Amsterdam, Netherlands; 2023.
. Machine learning on combined neuroimaging and plasma biomarkers for triaging participants of secondary prevention trials in Alzheimer’s Disease. In Alzheimer's Association International Conference. 2021.
. MRI-Based Screening of Preclinical Alzheimer's Disease for Prevention Clinical Trials. Journal of Alzheimer's Disease. 2018;64(4).
. NeAT: a nonlinear analysis toolbox for neuroimaging. Neuroinformatics. 2020;.
. Prediction of amyloid pathology in cognitively unimpaired individuals using voxelwise analysis of longitudinal structural brain MRI. Alzheimer's Research & Therapy. 2019;11(1).
. Prediction of amyloid pathology in cognitively unimpaired individuals using structural MRI. In Alzheimer's Association International Conference. 2021.
. Projection to Latent Spaces disentangles pathological effects on brain morphology in the asymptomatic phase of Alzheimer’s disease. Frontiers in Neurology, section Applied Neuroimaging. 2020;11.
. Shared latent structures between imaging features and biomarkers in early stages of Alzheimer's disease. In Workshop on Predictive Intelligence in Medicine (PRIME), MICCAI. Granada, Spain; 2018.
. Shared Latent Structures Between Imaging Features and Biomarkers in Early Stages of Alzheimer’s Disease. In PRedictive Intelligence in MEdicine. Springer International Publishing; 2018. pp. 60-67.
. Shared latent structures between imaging features and biomarkers in early stages of Alzheimer's disease: a predictive study. IEEE Journal of Biomedical and Health Informatics. 2019;.
. Structural Networks for Brain Age Prediction. In Medical Imaging with Deep Learning (MIDL 2022). 2022.
. Voxelwise nonlinear regression toolbox for neuroimage analysis: Application to aging and neurodegenerative disease modeling. In NIPS 2016 Workshop on Machine Learning for Health. 2016. (1.6 MB)
.