Advances in the Study of Multimodal Neuroimaging in the Early Diagnosis of Alzheimers Disease
Abstract
challenge to Chinas aging society. Effective early treatment of AD plays a crucial role in delaying disease progression and improving patient
outcomes. Multimodal neuroimaging techniques can provide in-depth research on the mechanisms of AD from structural, functional, and metabolic perspectives, laying the foundation for early diagnosis and treatment. This project aims to build upon previous work by using multimodal imaging methods, such as magnetic resonance imaging (PET), to investigate their role in the early diagnosis of AD, offering new insights
for its early diagnosis and treatment.
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[1] Zhang Shuo, Zhang Rong, Guo Yingjie, et al. Research on an Alzheimer's disease auxiliary diagnosis model based on 3D residual network [J]. Chinese Journal of Health Statistics, 2024, 41(06):883-888+892.
[2] Zhong Haijie, Wu Xiaohong, Qing Linbo, et al. Classification of Alzheimer's disease based on multimodal brain imaging [J]. Electronic
Measurement Technology, 2024, 47(23):134-143.
[3] Cui Jing, Yang Hui, Qin Yao, et al. Classification of Alzheimer's disease based on multimodal data integration [J]. Modern Preventive
Medicine, 2024, 51(10):1889-1894+1920.
[4] Zhang Yingteng. Advances in Multimodal Imaging Research of Alzheimer's Disease Based on Machine Learning and Brain Networks [J].
Journal of Molecular Imaging, 2023, 46(05):934-937.
[5] Peng Sirui, Gao Rong, et al. Advances in Multimodal Neuroimaging Research on Subjective Cognitive Function Decline [J]. Neurological Injury and Functional Reconstruction, 2023, 18(12):796-799.
DOI: http://dx.doi.org/10.70711/pmr.v2i6.7252
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