Machine Learning for Neurodegenerative Disorders
CRC Press (Verlag)
978-1-032-66093-6 (ISBN)
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This book explores the application of machine learning to the understanding, early diagnosis, and management of neurodegenerative disorders. With a specific focus on its role in ongoing clinical trials, the book covers essential topics such as data collection, pre-processing, feature extraction, model development, and validation techniques. It delves into the applications of neuroimaging techniques like MRI, CT, and PET in the diagnosis and understanding of neurodegenerative disorders. Additionally, the book examines various machine learning algorithms employed for biomarker discovery in neurodegenerative disorders. It highlights the role of neuroinformatics and big data analysis in advancing the understanding and management of neurodegenerative disorders. Furthermore, the book reviews future prospects and presents the ethical considerations and regulatory challenges associated with implementing machine learning approaches in the diagnosis, treatment, and prevention of neurodegenerative disorders. This comprehensive resource is intended for neuroscientists, students, researchers, and neurologists to understand the emerging scope of machine learning in neurodegenerative disorders.
Seasonal Blurb
This book explores the application of machine learning to the understanding, early diagnosis, and management of neurodegenerative disorders. With a specific focus on its role in ongoing clinical trials, the book covers essential topics such as data collection, pre-processing, feature extraction, model development, and validation techniques. It delves into the applications of neuroimaging techniques like MRI, CT, and PET in the diagnosis and understanding of neurodegenerative disorders. This comprehensive resource is intended for neuroscientists, students, researchers, and neurologists to understand the emerging scope of machine learning in neurodegenerative disorders.
Short Blurb
This book explores the application of machine learning to the understanding, early diagnosis, and management of neurodegenerative disorders. This comprehensive resource is intended for neuroscientists, students, researchers, and neurologists to understand the emerging scope of machine learning in neurodegenerative disorders.
Dr. Biswajit Jena is an Assistant Professor in the Department of Computer Science and Engineering at ITER, SOA, Bhubaneswar, India. He received his Ph.D. from IIIT-Bhubaneswar, India, in Biomedical Image analysis and his M.Tech. degree in Computer Science and Engineering from NIT, Rourkela, India. His broad research interests are in Biomedical Image Processing, Neuro-Oncology, Radiogenomics, Machine Learning, and Deep Learning. Dr. Sanjay Saxena is an Assistant Professor in the Department of Computer Science and Engineering at IIIT, Bhubaneswar, India. He completed his postdoctoral research in AI in the Biomedical Imaging Lab, Perelman School of Medicine, University of Pennsylvania, USA, and his Ph.D. from IIT BHU, Varanasi, India. His broad area of research is implementing AI-based methods in Radiomics and Radiogenomics studies of cancer. He has edited several books and published more than 50 research articles in peer-reviewed international journals and conferences. He is also a reviewer and on the editorial board of various international peer-reviewed journals. He is also an IEEE Professional Member. Dr. Sudip Paul is currently an Assistant Professor and Teacher in Charge in the Department of Biomedical Engineering, School of Technology, North-Eastern Hill University (NEHU), Shillong, India. He completed his post-doctoral research at the School of Computer Science and Software Engineering, The University of Western Australia, Perth, and his Ph.D. degree from the Indian Institute of Technology (Banaras Hindu University), Varanasi, with a specialization in Electrophysiology and brain signal analysis. Dr. Sudip has published more than 80 International journal and conference research articles. He has been granted four patents, and another five are under review. He has edited several books and is a member of different Societies and professional bodies, including IAN, APSN, ISN, IBRO, SNCI, SfN, IEEE, and IAS. He received many awards, especially the World Federation of Neurology (WFN) traveling fellowship, the Young Investigator Award, the IBRO Travel Awardee, and the ISN Travel Awardee.
1. Introduction to Brain Diseases. 2. Introduction to Machine Learning for Neurodegenerative Disorders. 3. Multi-modal Neuroimaging Techniques and Fusion in Neurodegenerative Disorders. 4. Data Collection and Pre-processing for Neurodegenerative Disorders. 5. Machine Learning Fundamentals for Analysis of Neurodegenerative Disorders. 6. Deep Learning in Neurodegenerative Disorder. 7. Harnessing the Power of Neuroinformatics and Big Data Analysis against Neurodegenerative Disorders. 8. Machine Learning Applications in Neurodegenerative Diseases. 9. Machine Learning in Stroke Analysis and Rehabilitation. 10. Biomarker Identification in Neurodegenerative Disorders through Machine Learning. 11. Future Directions and Challenges in Machine Learning Approaches for Analysis of Neurodegenerative Disorders
| Erscheint lt. Verlag | 20.5.2025 |
|---|---|
| Reihe/Serie | Artificial Intelligence in Biomedical Image Processing |
| Zusatzinfo | 21 Tables, black and white; 64 Line drawings, color; 8 Line drawings, black and white; 64 Illustrations, color; 8 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 178 x 254 mm |
| Themenwelt | Medizin / Pharmazie ► Physiotherapie / Ergotherapie ► Orthopädie |
| Naturwissenschaften ► Biologie ► Humanbiologie | |
| Naturwissenschaften ► Biologie ► Zoologie | |
| Technik ► Elektrotechnik / Energietechnik | |
| Technik ► Medizintechnik | |
| ISBN-10 | 1-032-66093-7 / 1032660937 |
| ISBN-13 | 978-1-032-66093-6 / 9781032660936 |
| Zustand | Neuware |
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