A new report urges equitable development and oversight of AI in neurological imaging to avoid worsening healthcare disparities.
Key Details
- 1UCLA Health and collaborators published a Neurology journal report assessing AI's dual impact in neurological care.
- 2AI already aids doctors in classifying brain tumors and stroke imaging for faster decisions.
- 3Researchers highlight risks for bias due to underrepresentation of certain groups in datasets.
- 4Three guiding principles recommended: diverse stakeholder input, AI education for neurologists, and strong independent governance.
- 5The aim is for AI to advance equity, particularly in resource-limited and underrepresented communities.
- 6The literature review involves experts from healthcare, FDA, and AI industry.
Why It Matters

Source
EurekAlert
Related News

AI Decision Support Proves Helpful, Yet Contentious, in Emergency Medicine
Researchers found that AI-driven decision support improved correct decision rates among emergency care doctors, but physician acceptance of AI recommendations remains split.

Machine Learning and 3D Imaging Reveal Magma Dynamics Beneath Santorini
Researchers used machine learning and 3D imaging to map the cause of Santorini's 2025 seismic unrest, revealing dynamic magma dike activity.

Advances in Multimodal Imaging and AI for Radiation-Induced Brain Injury
A state-of-the-art review highlights the use of multimodal imaging and AI to improve diagnosis and management of radiation-induced brain injury (RIBI).