Bioethical paradigms and risks of integrating artificial intelligence algorithms into clinical decision-making in neurology

Abstract

The introduction of artificial intelligence (AI) systems and deep learning methods into neurological practice, particularly for processing neuroimaging datasets and electroencephalography patterns, is driving structural transformations in clinical decision-making algorithms. This process necessitates a critical analysis of classical bioethical paradigms to minimize legal and iatrogenic risks.