Artificial intelligence for traumatic brain injury imaging: a translational review from algorithm development to clinical implementation

Abstract

AI is poised to revolutionize TBI neuroimaging by increasing diagnostic objectivity, efficiency, and prognostic precision. Successful clinical translation, however, requires overcoming key challenges related to data heterogeneity, model interpretability, and workflow integration. Future efforts must prioritize the generation of high-quality multi-center datasets, the development of explainable AI, and-most critically-the execution of prospective trials with patient outcome endpoints. Collaborative, interdisciplinary research is essential to translate these technological advances into tangible improvements in TBI care and recovery.

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