Artificial intelligence in neuroimaging: Opportunities and ethical challenges

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, leadin...

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Published in:Brain & spine 2024, Vol.4, p.102919, Article 102919
Main Authors: Brahma, Neha, Vimal, S.
Format: Article
Language:English
Subjects:
Algorithmic bias
Artificial intelligence
Data privacy
Ethical challenges
Neurodegenerative diseases
Neuroimaging
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description 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.
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subjects Algorithmic bias
Artificial intelligence
Data privacy
Ethical challenges
Neurodegenerative diseases
Neuroimaging
title Artificial intelligence in neuroimaging: Opportunities and ethical challenges
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