Development of an artificial intelligence-based convolutional neural network for sellar barrier classification using magnetic resonance imaging

Abstract

The proposed AI model significantly enhances the preoperative classification of sellar barriers, contributing to improving surgical planning and reducing complications. While the "black box" nature of AI poses challenges, integrating explainability modules and expanding datasets can further increase clinical trust and applicability. This study underscores the transformative potential of AI in neurosurgical practice, paving the way for precise and reliable diagnostics in managing pituitary lesions.

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