AAFITN/ANZSNR 2010: Asian-Australasian Federation of Interventional and Therapeutic Neuroradiology & Australian & New Zealand Society of Neuroradiology

AAFITN/ANZSNR 2010:亚洲-澳大利亚介入和治疗神经放射学联合会及澳大利亚和新西兰神经放射学会

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Abstract

Artificial intelligence (AI) has great potential to increase accuracy and efficiency in many aspects of neuroradiology. It provides substantial opportunities for insights into brain pathophysiology, developing models to determine treatment decisions, and improving current prognostication as well as diagnostic algorithms. Concurrently, the autonomous use of AI models introduces ethical challenges regarding the scope of informed consent, risks associated with data privacy and protection, potential database biases, as well as responsibility and liability that might potentially arise. In this manuscript, we will first provide a brief overview of AI methods used in neuroradiology and segue into key methodological and ethical challenges. Specifically, we discuss the ethical principles affected by AI approaches to human neuroscience and provisions that might be imposed in this domain to ensure that the benefits of AI frameworks remain in alignment with ethics in research and healthcare in the future.

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