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Filters: Author is Raffaele Cacciaglia  [Clear All Filters]
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B
Cumplido-Mayoral I, García-Prat M, Operto G, Falcon C, Shekari M, Cacciaglia R, et al.. 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.
Cumplido-Mayoral I, García-Prat M, Operto G, Falcon C, Shekari M, Cacciaglia R, et al.. 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. eLife. 2023;12.
Cumplido-Mayoral I, Shekari M, Salvadó G, Operto G, Cacciaglia R, Falcon C, et al.. 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.
Cumplido-Mayoral I, Brugulat-Serrat A, Sánchez-Benavides G, González-Escalante A, Anastasi F, Mila-Aloma M, et al.. 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.
Cumplido-Mayoral I, Mila-Aloma M, Falcon C, Cacciaglia R, Minguillon C, Fauria K, et al.. Brain-age prediction and its associations with glial and synaptic CSF markers. In Alzheimer's Association International Conference. Amsterdam, Netherlands; 2023.
N
Cumplido-Mayoral I, Sánchez-Benavides G, Alomà MMilà, Falcon C, Cacciaglia R, Minguillon C, et al.. Neuroimaging-derived biological brain age and its associations with glial reactivity and synaptic dysfunction cerebrospinal fluid biomarkers. Molecular psychiatry. 2025;.
S
Pina O, Cumplido-Mayoral I, Cacciaglia R, González-de-Echávarri JMaría, Gispert JD, Vilaplana V. Structural Networks for Brain Age Prediction. In Medical Imaging with Deep Learning (MIDL 2022). 2022.

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