Deep learning combining FDG-PET and neurocognitive data accurately predicts MCI conversion to Alzheimer's dementia 3-year post MCI diagnosis

Deep learning combining FDG-PET and neurocognitive data accurately predicts MCI conversion to Alzheimer's dementia 3-year post MCI diagnosis

Introduction: This study reports a novel deep learning approach to predict mild cognitive impairment (MCI) conversion to Alzheimer's dementia (AD) within three years using whole-brain fluorodeoxyglucose (FDG) positron emission tomography (PET) and cognitive scores (CS). Methods: This analysis c...

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Bibliographic Details
Main Authors: Eric Cao, Da Ma, Siddharth Nayak, Tim Q. Duong
Format: Article
Language:English
Published: Elsevier 2023-10-01
Series:Neurobiology of Disease
Subjects:
Positron emission tomography
Mild cognitive impairment
Machine learning
Artificial intelligence
Dementia
MRI
Online Access:http://www.sciencedirect.com/science/article/pii/S0969996123003261

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http://www.sciencedirect.com/science/article/pii/S0969996123003261

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