MCI progression classification for early diagnosis of Alzheimer’s disease using machine learning and deep learning methods

Thesis

Alzheimer’s disease (AD), the most common cause of dementia, affects more than 520,000 people in the UK. It is a progressive disease and its causes still remain unclear. Besides the traditional neuropsychological test, imaging biomarkers are playing an increasingly important role for AD detection and especially for early stage diagnosis including prediction of the transition from mild cognitive impairment (MCI) to AD. The use of structural imaging such as T1 MRI for AD diagnosis has been w...

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Authors: Yan, Y

• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Language: English
• Keywords: Alzheimer's disease; Machine learning; Deep learning
• Subjects: Biomedical Engineering