碩士 / 國立中山大學 / 電機工程學系研究所 / 107 / Alzheimer’s disease has gradually affected human beings around the world. It not only causes the decay of memory, but may also decreases other cognitive functions. At present, most doctors use the and outpatient data to determine whether a patient has a disease. Because the judgment process involves the patient’s response and the doctor’s subjective decision, the resulting diagnosis can be questionable. This study intends to establish an automatic identification system which can help doctors to determine the Alzheimer’s disease based on the clinical and fMRI information of the patient from Kaohsiung Medical University (KMU). About the technology of the system, we will divide it into three-stage data pre-processing, feature extraction(Mutual Information, Pearson, Linear Discriminant Analysis), classification model(Learning Vector Quantization, Support Vector Machine), and select the best combination through the experimental results for Clinical Dementia Rating to become our system. We will also explore whether the results of Covariate correction for age, education affect the doctor’s judgment and provide doctors with more important features for patients.
| Identifer | oai:union.ndltd.org:TW/107NSYS5442104 |
| Date | January 2019 |
| Creators | Ching-Sheng Tu, 塗景盛 |
| Contributors | Shie-Jue Lee, 李錫智 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 41 |
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