title: Domain transfer learning for MCI conversion prediction.
abstract: In recent studies of Alzheimer's disease (AD), it has increasing attentions in identifying mild cognitive impairment (MCI) converters (MCI-C) from MCI non-converters (MCI-NC). Note that MCI is a prodromal stage of AD, with possibility to convert to AD. Most traditional methods for MCI conversion prediction learn information only from MCI subjects (including MCI-C and MCI-NC), not from other related subjects, e.g., AD and normal controls (NC), which can actually aid the classification between MCI-C and MCI-NC. In this paper, we propose a novel domain-transfer learning method for MCI conversion prediction. Different from most existing methods, we classify MCI-C and MCI-NC with aid from the domain knowledge learned with AD and NC subjects as auxiliary domain to further improve the classification performance. Our method contains two key components: (1) the cross-domain kernel learning for transferring auxiliary domain knowledge, and (2) the adapted support vector machine (SVM) decision function construction for cross-domain and auxiliary domain knowledge fusion. Experimental results on the Alzheimer's Disease neuroimaging initiative (ADNI) database show that the proposed method can significantly improve the classification performance between MCI-C and MCI-NC, with aid of domain knowledge learned from AD and NC subjects.
authors.affiliation: Dept. of Computer Science and Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China. cb729@nuaa.edu.cn
authors.forename: Bo
authors.initials: B
authors.lastname: Cheng
authors.forename: Daoqiang
authors.initials: D
authors.lastname: Zhang
authors.forename: Dinggang
authors.initials: D
authors.lastname: Shen
mesh_terms: D000465:Algorithms; D000544:Alzheimer Disease / Q000175:diagnosis* / Q000503:physiopathology; D019540:Area Under Curve; D001185:Artificial Intelligence; D001931:Brain Mapping / Q000379:methods; D003072:Cognition Disorders / Q000473:pathology; D060825:Cognitive Dysfunction / Q000175:diagnosis* / Q000473:pathology; D003952:Diagnostic Imaging / Q000379:methods; D018450:Disease Progression; D006801:Humans; D019359:Knowledge; D015203:Reproducibility of Results; D012984:Software; D014163:Transfer, Psychology