Modular feature selection method for brain disease classification
A feature selection method and disease classification technology, applied in the field of modular feature selection, can solve problems such as ignoring topology and disaster of dimensionality
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[0033] In order to deepen the understanding of the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments, which are only used to explain the present invention and do not limit the protection scope of the present invention.
[0034] Such as figure 2 and image 3 As shown, a modular feature selection method for brain disease classification, the steps are as follows:
[0035] 1. Data acquisition and data preprocessing: In the example, using a data set from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, a total of 174 subjects (48 normal controls (NCs), 95 MCI and 31 AD) conducted 563 scans. It is worth noting that the subjects in this study were scanned once or more times with an interval of at least half a year. Therefore, the 563 scans can be divided into 154 cases of NC, 310 cases of MCI (eMCI 165 cases, lMCI 145 cases) and AD 99 cases, then, the rs-fMRI scans of all...
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