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P3‐185: Prediction of MCI to Alzheimer's conversion based on tensor‐based morphometry and kernel support vector machine
Author(s) -
Zhang Yudong,
Dong Zhengchao,
Wang Shuihua,
Ji Genlin,
Phillips Preetha
Publication year - 2015
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2015.06.1556
Subject(s) - pattern recognition (psychology) , support vector machine , artificial intelligence , voxel , cognitive impairment , kernel (algebra) , kernel principal component analysis , white matter , magnetic resonance imaging , principal component analysis , computer science , nuclear medicine , mathematics , medicine , kernel method , psychology , neuroscience , cognition , radiology , combinatorics
large ICV group, but the difference was not statistically significant. The rates of cognitive decline and brain atrophy were similar in all other subgroups. Conclusions:Our results show that during the MCI stage, the progression of brain atrophy and subsequent cognitive decline accelerate in individuals with large ICV, and thus shortens the duration of the MCI stage in these subjects. Therefore, within a group of MCI subjects, it would seem as if they progress to AD more rapidly than their counterparts. This has important implications for clinicians. As more and more patients visit clinics at the MCI stage, clinicians should warn those with large ICVof faster decline, and possibly urge the patient more strongly to take part in lifestyle changes.