Clinician perspectives on explainability in AI-driven closed-loop neurotechnology.

ABSTRACT: Artificial Intelligence (AI) holds promise for advancing the field of neurotechnology and accelerating its clinical translation. AI-driven clinical neurotechnologies leverage the power of non-linear algorithms to analyze complex brain data and enable adaptive, closed-loop neurostimulation. Despite these promises, the integration of AI into clinical practice remains limited, with lack of explainability being commonly cited as one main obstacle. This raises the question of whether opacity and lack of explainability also hinder the adoption of AI in closed-loop medical neurotechnologies. We investigated the attitudes, informational needs and preferences of clinicians regarding AI-driven closed-loop neurotechnologies and explored what forms of explanation they consider necessary for clinical u

SUBMITTER: Schopp L 

PROVIDER: S-EPMC12494947 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature