Harnessing artificial intelligence for the diagnosis and treatment of neurological emergencies: a comprehensive review of recent advances and future directions

Abstract

Artificial intelligence (AI) is rapidly transforming the landscape of neurology, offering innovative solutions for diagnosing and managing emergent neurological conditions such as stroke, traumatic brain injury, and acute spinal cord injury. This review critically examines the recent advancements in AI applications within the field of neurology, emphasizing both the potential and limitations of these technologies. While AI demonstrates remarkable accuracy and speed in diagnostic imaging, outcome prediction, and personalized treatment plans, its integration into clinical practice remains challenged by ethical concerns, infrastructural limitations, and the "black box" nature of many AI algorithms. The review highlights the current gaps in literature, particularly the limited research on AI's use in low-resource settings and its generalizability across diverse populations. Moreover, the review underscores the need for more longitudinal studies to assess the long-term efficacy of AI-driven interventions and calls for greater transparency in AI systems to enhance trust among clinicians. Future directions for AI in neurology emphasize the importance of interdisciplinary collaboration, regulatory oversight, and the development of equitable AI models that can benefit all patient populations. This review provides a balanced and comprehensive overview of AI's role in neurology, offering insights into both the opportunities and challenges that lie ahead.

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