Unlock the future of technology and medicine with this essential book that provides a comprehensive, perceptive study of Brain Informatics, detailing how computational approaches are revolutionizing our understanding of the brain and driving innovations in AI, robotics, and personalized healthcare.
Brain informatics sits at the intersection of information technology and neuroscience, using innovations from both fields to deepen our understanding of the human brain. Through tools like EEG and fMRI, researchers have gained new insights into cognition, behavior, and neurological disorders, paving the way for treatments, personalized medicine, and diagnostic advances. The integration of brain-computer interfaces and machine learning further expands possibilities in areas such as AI, robotics, healthcare, and human–machine interaction.
This book offers a perceptive study of the relationship between neuroscience and IT, exploring the significant implications of computational approaches in solving the secrets of the human brain. Navigating through topics such as brain anatomy, cognitive processes, and computer models of brain activity, it provides a thorough overview of the fundamental concepts that underpin brain informatics research. It also looks at real-world applications in a variety of fields, including customized medicine, healthcare diagnostics, instructional technology, and artificial intelligence systems inspired by the human brain. This essential guide offers a comprehensive view of the revolutionary potential of brain informatics influencing the future of information technology.
Readers will find this volume:
- Explores the intersection of neuroscience and informatics with practical applications;
- Provides insights into cutting-edge research and technologies shaping brain-computer interaction;
- Features contributions from leading experts in brain informatics and cognitive technologies.
Audience
Researchers and professionals in the fields of neuroscience, cognitive science, artificial intelligence, and data analytics.
Anamika Ahirwar, PhD is a Professor in the Department of Computer Science and Engineering at the Compucom Institute of Technology and Management, Jaipur, Rajasthan, India, with 21 years of experience in teaching and research. She has published more than 70 research papers in reputed national and international journals and conferences, five patents, and authored several books. Her research areas include medical imaging, data mining, celestial sound, Internet of Things, and machine learning.
Ruby Bhatt, PhD is an assistant professor in the Department of Computer Science at Medi-Caps University, Indore, India. She has authored several research papers in refereed journals and more than 15 conference papers on security issues in wireless sensor networks and optimization techniques. Her areas of interest include wireless sensor networks, artificial intelligence, data mining, and data analytics.
D. Dhanya, PhD is an Associate Professor in the Department of Artificial Intelligence and Data Science at the Mar Ephraem College of Engineering and Technology, Marthandam, India, with more than ten years of teaching experience. She has published various research papers in esteemed refereed international journals and presented her research at various international conferences. Her research focuses on cloud computing, evolutionary algorithms, artificial intelligence, and wireless sensor networks.
Roshani Choudhary, PhD is highly experienced in the development of classification algorithms for solving various classification problems. With more than six years of teaching and research experience, her research interests include writing machine learning algorithms and codes for solving real-life problems and the development of complex neural networks.
