AI-Driven Alzheimer's Disease Detection and Prediction
IGI Global (Verlag)
979-8-3693-3605-2 (ISBN)
Alzheimer's disease (AD) poses a significant global health challenge, with an estimated 50 million people affected worldwide and no known cure. Traditional methods of diagnosis and prediction often rely on subjective assessments. They are limited in detecting the disease early, leading to delayed intervention and poorer patient outcomes. Additionally, the complexity of AD, with its multifactorial etiology and diverse clinical manifestations, requires a multidisciplinary approach for effective management. AI-Driven Alzheimer's Disease Detection and Prediction offers a groundbreaking solution by leveraging advanced artificial intelligence (AI) techniques to enhance early diagnosis and prediction of AD. This edited book provides a comprehensive overview of state-of-the-art research, methodologies, and applications at the intersection of AI and AD detection. By bridging the gap between traditional diagnostic methods and cutting-edge technology, this book facilitates knowledge exchange, fosters interdisciplinary collaboration, and contributes to innovative solutions for AD management. It also benefits data scientists, engineers, policymakers, and professionals in the pharmaceutical and biotechnology industries. Graduate students interested in healthcare and technology will find accessible information on the latest developments in AI-driven approaches to AD detection and prediction.
Umesh Kumar Lilhore is currently a Professor at the School of Computing Science & Engineering (CSE) at Galgotia University, Greater Noida. With over 19 years of teaching and 8 years of research experience, he has previously held positions at various renowned universities and colleges in India and abroad. Dr. Lilhore holds a Ph.D. and M.Tech in CSE and has completed his postdoctoral research at the Institute of Advanced Computing, University of Louisiana at Lafayette. He has a strong publication record with articles in reputed, peer-reviewed national and international Scopus journals and conferences. With Abhineet Anand's 23+ years of academic and administrative experience, his research includes the following field of endeavour: Cloud Computing, Cloud Security, Decision Tree, nearest neighbour method, Clustering, Rule induction, Optical Fibre Switching in Wavelength Multiplexing, Automata Theory. He has published more than 14 SCI, 53+ Scopus indexed papers, 20+ papers in International conference, 12 Intentional Journal, 3 National Journal, and 3 National Conference with 6 Book with prestigious publishers. Abhishek Kumar is currently working as an Assistant Director in the Computer Science & Engineering Department at Chandigarh University, Punjab, India. is doing Post-Doctoral Fellow in Ingenium Research Group Ingenium Research Group Lab, Universidad De Castilla- La Mancha, Ciudad Real, and Ciudad Real Spain. He has total Academic teaching experience of more than 12 years along with 2 years teaching assistantship. He has more than 160 publications in reputed, peer-reviewed National and International Journals, books & Conferences He has authored/Co-Authored 7 books published internationally and edited 39 books (Published & ongoing with IET, Elsevier, Wiley, IGI GLOBAL Springer, Apple Academic Press, De-Gruyter and CRC, etc. He is Patent holder and got Sir CV Raman National award for 2018 in young researcher and faculty Category from IJRP Group. He is acting as Series Editor for three books series, Quantum Computing with Degruyter Germany, Intelligent Energy System with Elsevier, & Mathematical Methods in the Digital Age: Computational Intelligence & Advancements. Satya Prakash Yadav is currently the Associate Professor of the Department of Computer Science and Engineering, G.L. Bajaj Institute of Technology and Management (GLBITM), Greater Noida (India) and has completed his Postdoctoral under the supervision Prof. (Dr.) Victor Hugo C. de Albuquerque, from Federal Institute of Education, Science and Technology of Ceará, Brazil. He has awarded his PhD degree from Dr. A.P.J. Abdul Kalam Technical University (AKTU) (formerly UPTU). Currently, 4 students are working for Ph.D. under my guidance. A seasoned academician having more than 17 years of experience, he has published four books (Programming in C, Programming in C++ and Blockchain and Cryptocurrency) under I.K. International Publishing House Pvt. Ltd. Including Distributed Artificial Intelligence: A Modern Approach, Published December 18, 2020 by CRC Press. He has undergone industrial training programs during which he was involved in live projects with companies in the areas of SAP, Railway Traffic Management Systems, and Visual Vehicles Counter and Classification (used in the Metro rail network design). He is an alumnus of Netaji Subhas Institute of Technology (NSIT), Delhi Universit Narayan Vyas , a Principal Research Consultant at AVN Innovations, is a distinguished academician and expert in advanced technologies. He cleared the NTA UGC NET & JRF in Computer Science & Applications on his first attempt, underscoring his academic excellence. With profound knowledge of the Internet of Things (IoT) and Mobile Application Development, he has trained students worldwide and authored numerous articles in reputable national and international Scopus-indexed conferences and journals. His research spans IoT, Remote Sensing, Machine Learning, Deep Learning, and Computer Vision. A sought-after keynote speaker, Mr. Vyas collaborates with leading publishers like Wiley, IGI Global, and DeGruyter on various book projects, marking his significant contribution to the field.
| Erscheinungsdatum | 22.08.2024 |
|---|---|
| Verlagsort | Hershey |
| Sprache | englisch |
| Maße | 216 x 279 mm |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Medizin / Pharmazie ► Gesundheitswesen | |
| Medizin / Pharmazie ► Medizinische Fachgebiete ► Geriatrie | |
| Studium ► 2. Studienabschnitt (Klinik) ► Anamnese / Körperliche Untersuchung | |
| Technik ► Medizintechnik | |
| ISBN-13 | 979-8-3693-3605-2 / 9798369336052 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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