2018
DOI: 10.1007/s12021-018-9381-1
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Cognitive Assessment Prediction in Alzheimer’s Disease by Multi-Layer Multi-Target Regression

Abstract: Accurate and automatic prediction of cognitive assessment from multiple neuroimaging biomarkers is crucial for early detection of Alzheimer's disease. The major challenges arise from the nonlinear relationship between biomarkers and assessment scores and the inter-correlation among them, which have not yet been well addressed. In this paper, we propose multi-layer multi-target regression (MMR) which enables simultaneously modeling intrinsic inter-target correlations and nonlinear input-output relationships in … Show more

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Cited by 24 publications
(13 citation statements)
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“…With this in mind, the optimal dMRI indices to include in a multimodal study may be those that contribute the greatest independent information beyond that available from anatomical MRI and other standard imaging modalities. Multivariate methods—such as machine learning (Zhou et al, 2017; Wang X. et al, 2018) and even deep learning (Liu et al, 2017)—may also help to extract and capitalize on features that predict clinical decline beyond those studied here.…”
Section: Discussionmentioning
confidence: 99%
“…With this in mind, the optimal dMRI indices to include in a multimodal study may be those that contribute the greatest independent information beyond that available from anatomical MRI and other standard imaging modalities. Multivariate methods—such as machine learning (Zhou et al, 2017; Wang X. et al, 2018) and even deep learning (Liu et al, 2017)—may also help to extract and capitalize on features that predict clinical decline beyond those studied here.…”
Section: Discussionmentioning
confidence: 99%
“…This algorithm type has received a lot of attention from the machine learning science community. It has already proven itself in a wide variety of real life applications [9] such as www.ijacsa.thesai.org health [10], [13], wind speed [11], heating load in buildings. Energy efficiency [12], natural language processing [14] and bioinformatics [15].…”
Section: State Of the Artmentioning
confidence: 99%
“…Moreover, in [20], the authors describe some computational tools for the prediction of chemical multi-target profiles and adverse outcomes with systems toxicology. In addition, in [21], a multi-layer multi-target regression is proposed for the prediction of cognitive assessment from multiple neuroimaging biomarkers, allowing an early detection of Alzheimer's disease. Finally, in the SMURF methodology [9], a panoramic prediction is contemplated for predicting the responses of a multi-stage treatment for the migraine.…”
Section: Related Workmentioning
confidence: 99%