Application of Neuroinformatics in Alzheimer’s Disease Research

Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by the gradual decline in cognitive function, and its complex pathological mechanisms remain incompletely understood. As an interdisciplinary field that integrates multimodal data, neuroinformatics has played a crucial role in Alzheimer’s disease research in recent years. This review systematically explores the application of neuroinformatics in Alzheimer’s disease research, covering key databases and resources (e.g., ADNI and GAAIN), imaging technologies (e.g., MRI, fMRI, EEG, PET), and data analysis algorithms (e.g., support vector machines, convolutional neural networks). Neuroinformatics techniques have provided new pathways for early diagnosis, risk prediction, and personalized treatment of Alzheimer’s disease by integrating imaging, genomic, behavioral, and clinical data to reveal changes in brain function and structure in AD patients. In the future, with the strengthening of big data platforms and international collaborations, neuroinformatics will further promote the development of precision medicine in Alzheimer’s disease and provide stronger support for new treatment strategies.