COVID-19 and Artificial Intelligence: Application of Health Technologies in Neurological Science and Practice During and post-Pandemic brings to light, both in theory and practice, newly available trends in design and use of robust systems and effective models for clinical practice using artificial intelligence. It also covers state-of-the-art case studies, technologies, and methodological approaches applied by researchers and medical practitioners to neurological patients’ care during and in preparedness to the aftermath of the COVID-19 pandemic.
Artificial intelligence and machine learning techniques have many advantages and characteristics which make them an effective instrument in treating patients with neurological disorders. This book discusses the use of technology in intelligent disease diagnosis, healthcare, and other domains related to neurological disorders such as Atkinson’s, Alzheimer’s, amyotrophic lateral sclerosis (ALS), epilepsy and seizures, spinal cord injury, ataxia, brain tumors, Parkinson's, and diverse stroke types.
It is a valuable resource for researchers, students and member of the biomedical and medical fields who want to learn more about the use of AI to better diagnose and treat patients.

• Covers emerging topics related to the intersection of AI and clinical practice, with special focus on neurological diseases.
• Encompasses several pure, hybrid, and applied machine learning systems that can be theoretically and practically used to identify, analyze, predict, and diagnose neurological diseases, particularly during the pandemic and in post-pandemic era.
• Discusses state-of-the-art case studies, technologies, and methodological approaches applied by researchers and medical practitioners in the care of neurological patients in challenging environments.