Proceedings of the National Academy of Sciences of the United States of America
Jan 3, 2023
The gap between chronological age (CA) and biological brain age, as estimated from magnetic resonance images (MRIs), reflects how individual patterns of neuroanatomic aging deviate from their typical trajectories. MRI-derived brain age (BA) estimates...
Previous research has shown the benefits of early detection and treatment of dementia. This detection is usually performed manually by one or more clinicians based on reports and psychometric testing. Machine learning algorithms provide an alternativ...
BACKGROUND: Alzheimer's disease has become one of the most common neurodegenerative diseases worldwide, which seriously affects the health of the elderly. Early detection and intervention are the most effective prevention methods currently. Compared ...
BACKGROUND: Social robots have demonstrated promising outcomes in terms of increasing the social health and well-being of people with dementia and mild cognitive impairment. According to the World Health Organization's Monitoring and assessing digita...
Computer methods and programs in biomedicine
Nov 30, 2022
BACKGROUND AND OBJECTIVE: Mild cognitive impairment (MCI) is a transitional state between normal aging and Alzheimer's disease (AD), and accurately predicting the progression trend of MCI is critical to the early prevention and treatment of AD. Brain...
Exploring individual brain atrophy patterns is of great value in precision medicine for Alzheimer's disease (AD) and mild cognitive impairment (MCI). However, the current individual brain atrophy detection models are deficient. Here, we proposed a fr...
Deep neural networks have been successfully applied to generate predictive patterns from medical and diagnostic data. This paper presents an approach for assessing persons with Alzheimer's disease (AD) mild cognitive impairment (MCI), compared with n...
Progress in neuro-psychopharmacology & biological psychiatry
Nov 14, 2022
OBJECTIVE: To develop and validate artificial intelligence models for the prediction of cognitive impairment in chronic kidney disease (CKD) patients using structural and functional brain network.
Physical and engineering sciences in medicine
Nov 10, 2022
The study aims to implement a convolutional neural network framework that uses the 18F-FDG PET modality of brain imaging to detect multiple stages of dementia, including Early Mild Cognitive Impairment (EMCI) and Late Mild Cognitive Impairment (LMCI)...
An objective biomarker to predict the outcome of isolated rapid eye movement sleep behavior disorder (iRBD) is crucial for the management. This study aimed to investigate cognitive signature of brain [F]FDG PET based on deep learning (DL) for evaluat...
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