@conference {cCasamitjanab,
	title = {Projection to Latent Spaces Disentangles Specific Cerebral Morphometric Patterns Associated to Aging and Preclinical AD},
	booktitle = {Alzheimer{\textquoteright}s Association International Conference},
	year = {2018},
	month = {07/2018},
	address = {Chicago, USA},
	abstract = {<p class="p1">Partial Least Squares (PLS) is a mathematical technique that relates two sets of observable variables by means of a few latent explanatory factors. The aim of this study is to use PLS to discover the associations between CSF biomarkers and structural brain imaging in preclinical AD and to disentangle their specific contribution from confounding demographic factors.<span class="Apple-converted-space">\&nbsp;</span>PLS is able to disentangle the cerebral morphometric patterns associated to preclinical AD stages from other demographic factors. Results with both cortical thickness and volumetric data present significant overlap, thus showing the robustness of this approach. Interestingly, volumetric data showed more significant correlations with CSF Abeta than cortical thickness.</p>},
	author = {Adri{\`a} Casamitjana and P. Petrone and M. Artigues and J.L. Molinuevo and J.D. Gispert and Ver{\'o}nica Vilaplana}
}
@article {aCasamitjana18,
	title = { Projection to Latent Spaces Disentangles Specific Cerebral Morphometric Patterns Associated to Aging and Preclinical AD},
	journal = {Alzheimer{\textquoteright}s \& Dementia: The Journal of the Alzheimer{\textquoteright}s Association },
	volume = {14},
	year = {2018},
	month = {07/2018},
	pages = {P869-P870},
	doi = {10.1016/j.jalz.2018.06.1111},
	author = {Adri{\`a} Casamitjana and P. Petrone and M. Artigues and J.L. Molinuevo and J.D. Gispert and Ver{\'o}nica Vilaplana}
}
