In the swiftly evolving field of artificial intelligence (AI), the technology's capability to revolutionize care processes in neurological disorders is notably significant. Neurological diseases, including Alzheimer's, Parkinson's, and multiple sclerosis, among others, account for substantial global morbidity, presenting intricate challenges in early diagnosis and effective treatment due to their complex pathophysiological nature. AI offers transformative solutions by utilizing extensive clinical, imaging, and genetic data to enhance diagnostic accuracy, forecast disease trajectory, and tailor treatment approaches, setting a new standard in patient care.

This Research Topic is dedicated to probing the frontiers of AI applications targeted at the diagnostics and treatment of neurological diseases. It seeks to delve into the formulation of cutting-edge algorithms, the development of prediction models for disease monitoring, and the customization of treatment methodologies to accelerate and refine patient care. Furthermore, it puts a spotlight on the synthesis of multi-modal datasets, crucial for amassing a holistic understanding of these disorders, and addresses the ethical dimensions of deploying AI in sensitive clinical settings.

To further explore these advanced applications, the scope of this Research Topic is centered on achieving comprehensive insights into:

o The integration of varied data into cohesive healthcare solutions,

o Enhancements in the interpretability of AI-driven outputs, and,

o Upholding the ethical standards in AI application.

We welcome contributions that cover a diverse spectrum of themes, including:

o AI algorithms optimized for neuroimaging analysis (e.g., MRI, CT, fMRI, EEG)

o Predictive AI models for early detection and disease progression in neurological disorders

o AI in personalized treatment applications for tailoring therapy based on individual patient profiles

o Integration techniques for multi-modal data combining imaging, genomic, and clinical data

o Advances in ethical and explainable AI practices in clinical settings

o Secure AI technologies, such as federated learning, ensuring data privacy in neurology research

By addressing these areas, the research aims to foster significant advancements in the treatment and management of neurological disorders, enhancing both outcomes and quality of life for patients worldwide.

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Frontiers in Human Neuroscience

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