Abstract
The integration of artificial intelligence (AI) into neuroimaging represents a transformative shift in the diagnosis and treatment of neurodegenerative diseases. AI algorithms, particularly deep learning models, have demonstrated remarkable capabilities in analyzing complex neuroimaging data, leading to enhanced diagnostic accuracy and personalized treatment strategies. This letter discusses the opportunities AI presents in neuroimaging, including improved disease detection, predictive modeling, and treatment planning. However, the rapid adoption of AI technologies also raises significant ethical challenges. Issues such as algorithmic bias, data privacy, and the interpretability of AI-driven insights must be addressed to ensure that these technologies are used responsibly and equitably. As neuroimaging continues to evolve, a collaborative approach involving researchers, clinicians, and ethicists is essential to navigate these challenges and maximize the benefits of AI in improving patient outcomes in neurodegenerative diseases.