Overview of Current Technologies in Neurology with AI
Shikha Khullar, Kriti Sankhla · 2025
The integration of Artificial Intelligence (AI) into neurology is revolutionizing diagnosis, treatment, and management of neurological diseases. This chapter summarizes the current AI technologies applied in neurology, focusing on their implications on neuroimaging, disease diagnosis, neurophysiology, and personalized medicine. AI-based methods, including machine learning and deep learning, enhance the speed and accuracy of interpreting complex neurological data such as MRI, CT scan, and EEG recordings. These technologies enable early diagnosis of diseases such as Alzheimer&s;s disease, Parkinson&s;s disease, and epilepsy, allowing interventions to be undertaken in a timely manner. Further, emerging AI technologies, for example, natural language processing and brain-computer interfaces, are propelling neuroinformatics and patient care forward. There are also significant challenges to be addressed, including data privacy, model bias, and ethics. The chapter further discusses the potential future of federated learning and explainable AI (XAI) regarding providing more transparency as well as joint research. Supporting this discussion, we show, with the examples of effective real-world AI applications in stroke diagnosis, seizure forecast, and segmentation of brain tumors, how powerful AI could be for precision neurology. We end the chapter by talking about future directions, emphasizing the potential of AI in precision neurology and the fusion of AI-human collaborative systems. The analysis points out the revolutionary potential of AI in augmenting neurological care and the challenges and ethical concerns that come with it.