Machine learning model for predicting Amyloid-β positivity and cognitive status using early-phase 18F-Florbetaben PET and clinical features

Machine learning model for predicting Amyloid-β positivity and cognitive status using early-phase 18F-Florbetaben PET and clinical features

Abstract This study developed machine learning models to predict Aβ positivity in Alzheimer’s disease by integrating early-phase 18F-Florbetaben PET and clinical data to improve diagnostic accuracy. Furthermore, the study explored machine learning models to predict cognitive status from early-phase...

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Bibliographic Details
Main Authors: Dong Hyeok Choi, So Hyun Ahn, Yujin Chung, Jin Sung Kim, Jee Hyang Jeong, Hai-Jeon Yoon
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
18F-Florbetaben
Positron emission tomography
Early-phase
Amyloid-β
Cognitive status
Online Access:https://doi.org/10.1038/s41598-025-00743-7
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https://doi.org/10.1038/s41598-025-00743-7

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