A Shallow Review of Artificial Intelligence Applications in Brain Disease: Stroke, Alzheimer's, and Aneurysm

Abstract

Artificial Intelligence (AI) has emerged as a transformative tool in the field of neurology, offering innovative solutions for the diagnosis, treatment, and management of brain diseases. This review provides a focused examination of AI applications in three critical areas: stroke, Alzheimer's disease, and aneurysms. By analyzing recent advancements in machine learning algorithms, deep learning models, and neural networks, this paper highlights the significant impact of AI on improving diagnostic accuracy, predicting disease progression, and personalizing treatment plans. In the context of stroke, AI has been instrumental in enhancing imaging techniques and predicting patient outcomes. For Alzheimer's disease, AI-driven tools have shown promise in early detection and monitoring of disease progression through the analysis of neuroimaging and clinical data. In the case of aneurysms, AI applications have improved detection and risk assessment, facilitating timely and effective interventions. Despite these advancements, the review also addresses the ethical considerations, challenges, and limitations associated with the integration of AI in clinical practice. This shallow review aims to provide valuable insights for researchers, clinicians, and policymakers, fostering further exploration, and implementation of AI technologies in the management of brain diseases, and commercial platforms in brain disorders imaging.

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