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P4‐303: DISCOVERING SOURCES OF VARIABILITY IN AMYLOID DEPOSITION USING DATA‐DRIVEN ANALYSES
Author(s) -
Varatharajah Yogatheesan,
Lowe Val J.,
Przybelski Scott A.,
Schwarz Christopher G.,
Senjem Matthew L.,
Mielke Michelle M.,
Knopman David S.,
Petersen Ronald C.,
Graff-Radford Jonathan,
Iyer Ravi,
Jack Clifford R.,
Vemuri Prashanthi
Publication year - 2019
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.2019.06.3973
Subject(s) - amyloid (mycology) , principal component analysis , analysis of variance , dementia , variance (accounting) , amyloidosis , psychology , disease , medicine , pathology , artificial intelligence , computer science , accounting , business
baseline were negatively correlated with MMSE scores at followup (R1⁄40.175, p<0.005). Conclusions: The CARE index can predict the conversion of LOD to AD at the individual level during the 32-month follow-up period. It is suggested that the CARE index can be effectively applied to individual selection and early development of treatment strategies that delay or prevent the progression to AD.