Artificial Intelligence Strategies for Early Intervention in Neurodegeneration addresses the challenges surrounding the implementation of AI-based diagnoses of neurological disorders. These challenges include the lack of large, high-quality datasets, the necessity for standardization of data collection and analysis protocols, technical hurdles in developing accurate and reliable AI algorithms, and the requirement for regulatory approval and integration into clinical workflows. The content provides guidance to researchers on how to develop and integrate AI algorithms and biomarker analysis into their workflow, leading to a significant change in disease diagnosis. These techniques involve the analysis of physiological signals and images to identify patterns associated with specific diseases, and how AI algorithms can analyze medical imagery and movement and speech patterns to identify early signs of neurodegenerative diseases. The book advocates for non-invasive methods of diagnosis, which is significant progress in the field of patient-centered care by placing emphasis on the study of gait signals and other non-invasive indicators.

• Presents an interdisciplinary perspective from experts in biomedical engineering, artificial intelligence, and neurology
• Covers emerging research trends, providing a roadmap for researchers to contribute to the evolving field
• Highlighting the use of machine learning and artificial intelligence for automated diagnosis of neurological disorders