https://scholars.lib.ntu.edu.tw/handle/123456789/635481
標題: | Machine Learning-Based Classification of Subjective Cognitive Decline, Mild Cognitive Impairment, and Alzheimer's Dementia Using Neuroimage and Plasma Biomarkers | 作者: | Chiu, Shu-I Fan, Ling-Yun CHIN-HSIEN LIN TA-FU CHEN Lim, Wee Shin JYH-SHING JANG Chiu, Ming-Jang |
關鍵字: | Alzheimer’s disease spectrum; machine learning; mild cognitive impairment; neuroimage; plasma biomarker; subjective cognitive decline | 公開日期: | 7-十二月-2022 | 卷: | 13 | 期: | 23 | 起(迄)頁: | 3263 | 來源出版物: | ACS chemical neuroscience | 摘要: | Alzheimer's disease (AD) progresses relentlessly from the preclinical to the dementia stage. The process begins decades before the diagnosis of dementia. Therefore, it is crucial to detect early manifestations to prevent cognitive decline. Recent advances in artificial intelligence help tackle the complex high-dimensional data encountered in clinical decision-making. In total, we recruited 206 subjects, including 69 cognitively unimpaired, 40 subjective cognitive decline (SCD), 34 mild cognitive impairment (MCI), and 63 AD dementia (ADD). We included 3 demographic, 1 clinical, 18 brain-image, and 3 plasma biomarker (Aß1-42, Aß1-40, and tau protein) features. We employed the linear discriminant analysis method for feature extraction to make data more distinguishable after dimension reduction. The sequential forward selection method was used for feature selection to identify the 12 best features for machine learning classifiers. We used both random forest and support vector machine as classifiers. The area under the receiver operative curve (AUROC) was close to 0.9 between diseased (combining ADD and MCI) and the controls. AUROC was higher than 0.85 between SCD and controls, 0.90 between MCI and SCD, and above 0.85 between ADD and MCI. We can differentiate between adjacent phases of the AD spectrum with blood biomarkers and brain MR images with the help of machine learning algorithms. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/635481 | ISSN: | 1948-7193 | DOI: | 10.1021/acschemneuro.2c00255 |
顯示於: | 醫學院附設醫院 (臺大醫院) |
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