This book delves into the transformative potential of artificial intelligence (AI) and machine learning (ML) as game-changers in diagnosing and managing neurodisorder conditions. It covers a wide array of methodologies, algorithms, and applications in depth.
Computational Intelligence Algorithms for the Diagnosis of Neurological Disorders equips readers with a comprehensive understanding of how computational intelligence empowers healthcare professionals in the fight against neurodisorders. Through practical examples and clear explanations, it explores the diverse applications of these technologies, showcasing their ability to analyze complex medical data, identify subtle patterns, and contribute to the development of more accurate and efficient diagnostic tools. The authors delve into the exciting possibilities of AI-powered algorithms, exploring their ability to analyze various data sources like neuroimaging scans, genetic information, and cognitive assessments. They also examine the realm of ML for pattern recognition, enabling the identification of early disease markers and facilitating timely intervention. Finally, the authors also address the critical challenges of data privacy and security, emphasizing the need for robust ethical frameworks to safeguard sensitive patient information.
This book aims to spark a conversation and foster collaboration among researchers, clinicians, and technologists, and will assist radiologists and neurologists in making precise diagnoses with enhanced accuracy.
S. N. Kumar received his B.E. degree from the Department of Electrical and Electronics Engineering, Sun College of Engineering and Technology, in 2007, his M.E. degree in applied electronics from the Anna University of Technology, Tirunelveli, and his Ph.D. degree from the Sathyabama Institute of Science and Technology in 2019. He is currently an Associate Professor with the Department of Electrical and Electronics Engineering, Amal Jyothi College of Engineering, Kanjirappally, and his research areas include medical image processing and embedded systems.
Sherin Zafar is an Assistant Professor of Computer Science and Engineering at the School of Engineering Sciences and Technology, Jamia Hamdard University, with a decade of successful experience in teaching and research management. She specializes in wireless networks, soft computing, and network security.
Sameena Naaz is a Senior Lecturer at the Department of Computer Science, School of Arts, Humanities and Social Sciences at the University of Roehampton, London, UK, with more than 22 years of experience. She received her M.Tech. degree in Electronics with Specialization in Communication and Information Systems from Aligarh Muslim University in 2000 and completed her Ph.D. from Jamia Hamdard in the field of distributed systems in 2014. Her research interests include distributed systems, cloud computing, big data, machine learning, data mining, and image processing.
