ADNI Dataset

The Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset is a large, publicly available collection of neuroimaging, genetic, and clinical data used extensively to research Alzheimer's disease (AD) and its prodromal stage, mild cognitive impairment (MCI). Current research focuses on developing machine learning models, including convolutional neural networks (CNNs), support vector machines (SVMs), and more recently, large language models (LLMs) and transformer-based architectures, to improve the accuracy and efficiency of AD diagnosis and risk prediction, often leveraging features extracted from MRI scans. These efforts aim to identify robust biomarkers for early detection and disease progression monitoring, ultimately improving clinical diagnosis and treatment strategies. The ADNI dataset's impact lies in its facilitation of collaborative research and the development of advanced computational tools for understanding and managing AD.