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Classification of Structural MRI Images in Alzheimer's Disease from the Perspective of Ill-Posed Problems

Overview of attention for article published in PLOS ONE, October 2012
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Title
Classification of Structural MRI Images in Alzheimer's Disease from the Perspective of Ill-Posed Problems
Published in
PLOS ONE, October 2012
DOI 10.1371/journal.pone.0044877
Pubmed ID
Authors

Ramon Casanova, Fang-Chi Hsu, for the Alzheimer's Disease Neuroimaging Initiative Mark A. Espeland

Abstract

Machine learning neuroimaging researchers have often relied on regularization techniques when classifying MRI images. Although these were originally introduced to deal with "ill-posed" problems it is rare to find studies that evaluate the ill-posedness of MRI image classification problems. In addition, to avoid the effects of the "curse of dimensionality" very often dimension reduction is applied to the data.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
Unknown 76 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 18%
Student > Master 14 18%
Student > Ph. D. Student 12 15%
Student > Bachelor 6 8%
Other 5 6%
Other 13 17%
Unknown 14 18%
Readers by discipline Count As %
Medicine and Dentistry 12 15%
Psychology 9 12%
Computer Science 9 12%
Engineering 8 10%
Agricultural and Biological Sciences 6 8%
Other 18 23%
Unknown 16 21%