Prediction of Amyloid Positivity in Mild Cognitive Impairment Using Fully Automated Brain Segmentation Software.
Koung Mi KangChul-Ho SohnMin Soo ByunJun Ho LeeDahyun YiYounghwa LeeJun-Young LeeYu Kyeong KimBo Kyung SohnRoh-Eul YooTae Jin YunSeung Hong ChoiJi Hoon KimDong Young Leenull nullPublished in: Neuropsychiatric disease and treatment (2020)
Relative hippocampal volume measures provided by automated brain segmentation software can be useful for screening cerebral Aβ positivity in clinical practice for patients with amnestic MCI. The information may also help clinicians interpret structural MRI to predict outcomes and determine early intervention for delaying the progression to Alzheimer's disease dementia.
Keyphrases
- mild cognitive impairment
- deep learning
- cognitive decline
- cerebral ischemia
- clinical practice
- convolutional neural network
- resting state
- machine learning
- white matter
- subarachnoid hemorrhage
- high throughput
- randomized controlled trial
- magnetic resonance imaging
- functional connectivity
- blood brain barrier
- data analysis
- contrast enhanced
- brain injury
- palliative care
- computed tomography
- type diabetes
- health information
- adipose tissue
- multiple sclerosis
- metabolic syndrome
- social media