Abstract The convergence of artificial intelligence (AI) and neuroscience represents one of medicine's most profound intellectual partnerships. Neuronal architecture has inspired computational methods, while computational models, evolving from theoretical constructs to transformative clinical tools, are reshaping neurological practice. As AI systems attempt to augment diagnostic accuracy, treatment planning, and patient care, neurologists must develop fluency in these technologies to harness their potential while navigating their limitations and dangers. AI-related publications have exponentially increased in recent years, yet many neurologists lack the foundational computer science background needed to critically evaluate and most safely and effectively implement these tools in clinical practice. This article serves to outline the historical foundations linking neuroscience to computing, examine core concepts of the past and current AI landscape in neurology, and describe methodologies that aim to revolutionize neurological care.
📖 افتح في inklap 🔗 DOI 📮 اطلب بحثاً