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August 10, 2024Deleted JournalOpen Access

18F-FDG-PET-based deep learning for predicting cognitive decline in non-demented elderly across the Alzheimer’s disease clinical spectrum

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Authors

BSBeomseok SohnSCSeok Jong ChungJLJeong Ryong Lee

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Cite This Study

Sohn et al. (2024) studied this question.

synapsesocial.com/papers/68e5cc74b6db643587563070https://doi.org/10.1093/radadv/umae021
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Deep Learning-Based Amyloid PET Harmonization to Predict Cognitive Decline in Non-Demented Elderly2024
  2. 2Comparing a pre-defined versus deep learning approach for extracting brain atrophy patterns to predict cognitive decline due to Alzheimer’s disease in patients with mild cognitive symptoms2024 · 4 citations
  3. 3Feature integration of [18F]FDG PET brain imaging using deep learning for sensitive cognitive decline detection2026
  4. 4The use of individual-based FDG-PET volume of interest in predicting conversion from mild cognitive impairment to dementia2024 · 12 citations
  5. 5Using Deep Learning Techniques as an Attempt to Create the Most Cost-Effective Screening Tool for Cognitive Decline2024