Premium
IC‐P‐171: PREDICTING MCI‐TO‐AD CONVERSION USING NEUROIMAGING CLASSIFIER WITH ARTIFICIAL INTELLIGENCE (AI)
Author(s) -
Wang Lanbo,
Han Liang,
Wang Jianli,
Lu Jiaming,
Zhang Bing,
Zhu Bin,
Miller David J.,
Eslinger Paul J.,
Chai Junjie,
Pu Xiujuan,
Yang Qing X.
Publication year - 2018
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.2018.06.2238
Subject(s) - artificial intelligence , pattern recognition (psychology) , classifier (uml) , computer science , perceptron , neuroimaging , backpropagation , multilayer perceptron , artificial neural network , machine learning , medicine , psychiatry
signature of progression to Alzheimer’s dementia (HPS+), MCI subjects with a low-confidence prediction (Non-HPS+), and MCI subjects who were not flagged as hits (Negative) in a) ADNI1 and b) ADNI2. ADAS13: Alzheimer Disease Assessment Scale Cognitive. Significant differences are denoted by * for p <0.05 and ** for p< 0.001. Fig 1. Clinical characteristic of ANDI participants. Note: BL: baseline, 3yt: 3 years timepoint