The transforming power of artificial intelligence in neurological diseases: Present applications and future directions

Abstract

Recent advances in artificial intelligence (AI) for the diagnosis, treatment, and management of neurological disorders are revolutionizing the world of neurology. This review discusses the current state of AI in neurology in terms of enhanced diagnostic accuracy and disease monitoring, as well as new personalized strategies for diagnosis and treatment. AI-driven models analyze vast amounts of healthcare data, including genetic information and brain scans, to identify patterns and biomarkers that may be overlooked using traditional methods. Machine learning and deep learning algorithms have shown promise in predicting the onset and progression of conditions, such as epilepsy, multiple sclerosis, Parkinson’s disease, and Alzheimer’s disease. AI-based neuroimaging analysis also enables more precise characterization of brain structure, facilitating early detection and intervention. Furthermore, AI-powered tools improve patient care by enabling remote monitoring and supporting rehabilitation, thereby enhancing the quality of life of individuals with chronic neurological conditions. Despite these advancements, challenges remain, including concerns about algorithmic bias, data security, and the need for rigorous clinical validation. This paper provides a comprehensive overview of AI-driven innovations in neurology, addressing both their practical implications and ethical considerations while highlighting future research opportunities. The ultimate goal is to illustrate AI’s transformative impact on neurology, contributing to better patient outcomes and a deeper understanding of complex neurological disorders.

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