Artificial Intelligence in Brain Disorders
Academic Press Inc (Verlag)
978-0-443-27722-1 (ISBN)
- Noch nicht erschienen (ca. Juni 2026)
- Versandkostenfrei
- Auch auf Rechnung
- Artikel merken
As such, this book offers a detailed overview of AI and machine learning techniques relevant to neurological research.
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 completed his Master of Pharmacy (M. Pharm) in Pharmaceutics from Galgotias University, Greater Noida, India. He is currently an Assistant Professor in the Department of Pharmacy at Vivekanand Global University, where he is actively engaged in teaching and research. His research interests encompass various emerging and interdisciplinary fields, including nano-formulation, blockchain technology, the Internet of Things (IoT), machine learning, cancer biology, artificial intelligence, big data analytics, and neuroscience. Demonstrating a strong commitment to academic excellence, Mr. Singh has made significant contributions to the scientific community. 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.
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
| Erscheint lt. Verlag | 1.6.2026 |
|---|---|
| Verlagsort | San Diego |
| Sprache | englisch |
| Maße | 191 x 235 mm |
| Gewicht | 450 g |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Medizin / Pharmazie ► Physiotherapie / Ergotherapie ► Orthopädie | |
| Technik ► Medizintechnik | |
| ISBN-10 | 0-443-27722-2 / 0443277222 |
| ISBN-13 | 978-0-443-27722-1 / 9780443277221 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
| Haben Sie eine Frage zum Produkt? |
aus dem Bereich
