Autorentext
Dr. Pranav Kumar Prabhakar is currently working as a Professor in the Department of Biotechnology at Nagaland University, Kohima, Nagaland, India. He has been listed among the World's Top 2% Scientists (as published by Stanford University, USA, in 2021, 2022, 2023, and 2024). He earned his PhD in Biotechnology from IIT Madras. His primary research interests include elucidating molecular mechanisms and strategies for oral insulin delivery and mimicking signaling pathways in metabolic disorders (diabetes) using natural products. He is a member of the Royal Society of Chemistry and the Asia-Pacific Chemical, Biological & Environmental Engineering Society. He also serves as an editorial board member and reviewer for several reputed national and international journals. Dr. Pranav has received various honors, including a travel grant to attend ATTD 2009 in Greece, sponsored by the Indian Institute of Technology Madras and the Council for Scientific and Industrial Research (CSIR), and approved by the Department of Science and Technology (DST). He has published over 115 research articles in journals, authored or edited 17 books, contributed more than 40 book chapters, and delivered 9 oral and poster presentations at scientific meetings. Arun Kumar Singh has completed M. Pharm (Pharmaceutics) from Galgotias University, Greater Noida, India. Mr. Singh joined as an assistant professor in the Department of Pharmacy, Vivekanand Global University Jaipur Rajasthan 303012. His area of interest is in the area of Nano-formulation, Blockchain, IoT, Machine learning, Cancer, Artificial intelligence, Big data, and Neuroscience. He has authored one book with IOP publishing. He has published 5 chapters in big data with the prestigious River Publisher, in Denmark. He has also published 20 review papers among which two are in Biochimica et Biophysica Acta (BBA) Reviews on Cancer. He has published 26 books with different publishers like IOP, Elsevier, CRC PRESS, and Wiley. His strengths are research skills, innovation, leadership, decision-making, and positive thinking. His hard-working nature and devotion to their work make him distinguishable and extraordinary.

Prateek Agrawal is professor and deputy dean at the School of Computer Science & Engineering, Lovely Professional University, Phagwara, Punjab, India. His research areas include natural language processing, computer vision, video processing, expert systems, deep learning applications, and other related topics. He is a senior member of IEEE and core member of IEEE India Council for Sustainable Development Activity, and is also a member of different reputed organizations like IET, MIR lab, and IAENG among others. Dr. Agarwal has published over 70 research papers in Scopus/SCIE indexed journals and conferences, 60 national patents, five edited books, and 10 book chapters. He is book series editor of the IOP series on next generation computing, and is a reviewer for many SCIE journals like Multimedia tools and Applications, Plos One, PeerJ, Oxford computer science, IEEE Access, and Ambient Intelligent & Humanized Computing.

Radu Prodan is professor of distributed systems at the Institute of Information Technology (ITEC), University of Klagenfurt, Austria. He was an associate professor at the University of Innsbruck until 2018. His research interests include performance, optimization, and resource management tools for parallel and distributed systems, as well as middleware system tools for cloud, fog, and edge computing. He has participated in numerous projects, including coordinating the Horizon 2020 project ARTICONF. He has coauthored over 200 publications and received three IEEE best paper awards. He is a member of ACM.

Klappentext

Artificial Intelligence in Brain Disorders: Innovations in Diagnosis and Treatment focuses on the utilization of AI and machine learning to enhance current practices in the diagnosis and treatment of neurological disorders. Each chapter provides in-depth exploration of specific areas where AI can improve existing methodologies, offering practical guidance, case studies, and research findings that can be directly applied in the field. It explains the application of AI in diagnosing and treating major neurological illnesses and showcases the potential of AI in predicting diseases such as epilepsy and neurodegenerative disorders.

As such, this book offers a detailed overview of AI and machine learning techniques relevant to neurological research.

Inhalt

1. An Overview of Artificial Intelligence-Based Imaging Techniques
   
   2. Identification and evaluation of low-grade gliomas in the brain using machine learning
   3. Cognitive therapy for brain diseases using deep learning models
   4. Machine Intelligence in Clinical Neuroscience
   5. Brain Informatics, by NL Swathy, Department Of Pharmacy Practice
   6. Alzheimer's Disease Diagnosis using Artificial Intelligence
   7. AI-enabled assistance support to Alzheimer Patients
   8. Adolescents with serious depressive disorder: AI for detecting mental disorders
   9. Modelling cognitive impairment in Parkinson s patients using deep learning
   10. Parkinson’s disease diagnosis using AI
   11. Artificial Intelligence shaping the future of neurology practice
   12. Convergence of Artificial Intelligence and Neuroscience for Neurological Disorder Diagnosis
   13. Early detection and prediction of brain tumurs in human patients using deep learning
   14. Using deep learning to identify Brain tumors
   15. Combining artificial intelligence and neuroscience to diagnose and predict neurological diseases
   16. The role of AI in neuroethics and patients’ privacy