Hyun Kook Lim

Abstract Alzheimer’s disease (AD) accounts for 60–70% of the population with dementia. Mild cognitive impairment (MCI) is a diagnostic entity defined as an intermediate stage between subjective cognitive decline and dementia, and about 10–15% of people annually convert to AD. We aimed to investigate the most robust model and modality combination by combining multi-modality image features based on demographic characteristics in six machine learning models.

1. Introduction Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by a gradual and long-term decline in cognitive function [1]. A contemporary amyloid cascade hypothesis suggests that deposition of beta-amyloid (Aβ) peptide is an upstream event that is associated with downstream tau deposition, neurodegeneration, and eventual cognitive decline [2]. Clinico-pathophysiological changes associated with AD begin decades before clinical symptom onset [3].

Open AccessArticle by Sheng-Min Wang 1,2, Dong Woo Kang 1,3, Yoo Hyun Um 1,4, Sunghwan Kim 1,2, Chang Uk Lee 1,3 and Hyun Kook Lim 1,2,* 1 Department of Psychiatry, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea 2 Department of Psychiatry, Yeouido St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 07345, Republic of Korea 3 Department of Psychiatry, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of...