Meta Deep Learning Models for Human Neuroimaging

Curated Literature Overview
Erscheinungsjahr 2027
ISBN: 978-981-9233-51-9
Verlag: Springer Verlag, Singapore

Buch, Englisch, 244 Seiten, Format (B × H): 155 mm x 235 mm

This book presents the result of an innovative challenge, to create a systematic literature overview driven by machine-generated content. Questions and related keywords were prepared for the machine to query, discover, collate and structure by Artificial Intelligence (AI) clustering. The AI-based approach seemed especially suitable to provide an innovative perspective as the topics are indeed both complex, interdisciplinary and multidisciplinary. Springer Nature has published much on these topics in its journals over the years, so the challenge was for the machine to identify the most relevant content and present it in a structured way that the reader would find useful. The automatically generated literature summaries in this book are intended as a springboard to further discoverability. They are particularly useful to readers with limited time, looking to learn more about the subject quickly and especially if they are new to the topics. Springer Nature seeks to support anyone who needs a fast and effective start in their content discovery journey, from the undergraduate student exploring interdisciplinary content to Master- or PhD-thesis developing research questions, to the practitioner seeking support materials, this book can serve as an inspiration, to name a few examples. 

It is important to us as a publisher to make advances in technology easily accessible to our authors and find new ways of AI-based author services that allow human-machine interaction to generate readable, usable, collated, research content.

Zielgruppe

Research

Autoren/Hrsg.

Jabbar, M.A.

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen

Inhaltsverzeichnis

1. Methods, algorithms and applications of Meta learning in health care.- 2. Meta learning and Deep learning techniques for brain stroke detection.- 3. Advances in neuro imaging using cognitive meta learning.- 4. Deep reinforcement learning in neuroimaging.- 5. Meta Deep learning models for Parkinson disease.- 6. Meta learning and deep learning Models for Alzheimer Disease.- 7. Gene expression data using Deep learning.- 8. Transfer learning in neuroimaging.- 9. Issues, and Challenges in applying Deep learning models in neuroimaging.- 10. Meta deep learning models for brain disorder analysis.

Über Autor(innen)

M. A. Jabbar is a distinguished professional in the field of Computer Science and Engineering, specializing in Artificial Intelligence (AI) and Machine Learning (ML). He serves as Professor and Head of the Department of Computer Science and Engineering (AI & ML) at Vardhaman College of Engineering, Hyderabad, Telangana, India. His work focuses on advancing AI and ML, and his expertise and dedication have earned him numerous accolades. These include the and from the CSI Mumbai Chapter, the from the IEEE Hyderabad Section, and the from the IEEE Computer Society Chapter (2021). His significant research contributions span artificial intelligence, machine learning, and their interdisciplinary applications, establishing him as a leading figure in these domains. In addition to his research achievements, Dr. Jabbar holds senior memberships in globally recognized professional organizations such as the Association for Computing Machinery (ACM) and the Institute of Electrical and Electronics Engineers (IEEE). He is also a life member of the Computer Society of India (CSI) and the Indian Science Congress Association (ISCA).