AI-Driven Biomarkers in Neurology: A Narrative Review

The provided text outlines a narrative review detailing how artificial intelligence is revolutionizing the discovery of biomarkers for various neurological conditions. Traditional diagnostic methods often struggle with biological complexity and delayed detection, but AI algorithms can integrate vast, multimodal datasets to identify subtle disease patterns. The sources highlight significant progress in using machine learning and deep learning to improve the diagnosis and treatment of neurovascular, neurodegenerative, and neuro-oncological disorders. For instance, AI-driven models enhance stroke outcome predictions, identify intracranial aneurysms with high sensitivity, and detect early signs of Alzheimer’s disease. Despite these breakthroughs, the text notes that clinical translation faces challenges such as dataset bias, the need for prospective validation, and the importance of algorithmic transparency. Ultimately, the research suggests that AI-based biomarkers are essential for advancing precision neurology and personalizing patient care.