Generative AI in Neurodegenerative Disorders
Innovations, Views, and Obstacles
Herausgeber: Nag, Anindya; Karim, Asif; Hassan, Md. Mehedi
Generative AI in Neurodegenerative Disorders
Innovations, Views, and Obstacles
Herausgeber: Nag, Anindya; Karim, Asif; Hassan, Md. Mehedi
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This book explores the transformative power of AI in the domain of neurodegenerative diseases such as ALS, Parkinson's, and Alzheimer's. It explores AI-driven advancements in predictive analytics, biomarker discovery, drug development, and rehabilitation tools while addressing ethical, regulatory, and data privacy challenges.
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This book explores the transformative power of AI in the domain of neurodegenerative diseases such as ALS, Parkinson's, and Alzheimer's. It explores AI-driven advancements in predictive analytics, biomarker discovery, drug development, and rehabilitation tools while addressing ethical, regulatory, and data privacy challenges.
Produktdetails
- Produktdetails
- Verlag: River Publishers
- Seitenzahl: 452
- Erscheinungstermin: 14. Oktober 2025
- Englisch
- Abmessung: 240mm x 161mm x 29mm
- Gewicht: 840g
- ISBN-13: 9788743801757
- ISBN-10: 8743801757
- Artikelnr.: 74977844
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- gpsr@libri.de
- Verlag: River Publishers
- Seitenzahl: 452
- Erscheinungstermin: 14. Oktober 2025
- Englisch
- Abmessung: 240mm x 161mm x 29mm
- Gewicht: 840g
- ISBN-13: 9788743801757
- ISBN-10: 8743801757
- Artikelnr.: 74977844
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- gpsr@libri.de
Anindya Nag obtained an M.Sc. in Computer Science and Engineering from Khulna University in Khulna, Bangladesh, and a B.Tech. in Computer Science and Engineering from Adamas University in Kolkata, India. He is currently a Lecturer in the Department of Computer Science and Engineering at the Northern University of Business and Technology in Khulna, Bangladesh. His research focuses on health informatics, medical Internet of Things, neuroscience, and machine learning. He serves as a reviewer for numerous prestigious journals and international conferences. He has authored and co-authored about 42 publications, including journal articles, conference papers, and book chapters, and has co-edited five books. Md. Mehedi Hassan is a dedicated and accomplished researcher. He completed his Master of Science degree in computer science and engineering at Khulna University, Khulna, Bangladesh in 2024 and completed his B.Sc. degree in Computer Science and Engineering from North Western University, Khulna in 2022, where he excelled in his studies and demonstrated a strong aptitude for research. As the founder and CEO of The Virtual BD IT Firm and VRD Research Laboratory, Bangladesh, Mehedi has established himself as a highly respected leader in the fields of biomedical engineering, data science, and expert systems. He is a member of the prestigious IEE. Mehedi's research interests are broad and include important human diseases, such as oncology, cancer, and hepatitis, as well as human behavior analysis and mental health. He is highly skilled in association rule mining, predictive analysis, machine learning, and data analysis, with a particular focus on the biomedical sciences. Mehedi has published 74 articles in various international top journals and conferences and has published a book titled, ""Federated Deep Learning for Healthcare: A Practical Guide with Challenges and Opportunities"". His work has been well-received by the research community and has significantly contributed to the advancement of knowledge in his field. Additionally, he serves as an academic editor and a reviewer for 56 prestigious journals. Dr. Asif Karim is a Research Active Lecturer at Charles Darwin University, Australia. His research interests include applying machine intelligence to fields such as smart contracts and health informatics. Besides being an active researcher, He has considerable industry experience in IT, primarily in software engineering. In addition, He is also involved in active teaching to undergraduate and postgraduate students in a range of different computer science related courses. Dr. C Kishor Kumar Reddy is currently working as Associate Professor, Dept. of Computer Science and Engineering, Stanley College of Engineering and Technology for Women, Hyderabad, India and has research and teaching experience of more than 10 years. He has published more than 50 research papers in national and international conferences, book chapters, and journals indexed by Scopus and others. He is an author of two text books and has co-edited seven books. He acted as the special session chair for Springer FICTA 2020, 2022, SCI 2021, INDIA 2022 and IEEE ICCSEA 2020 conferences. He is the corresponding editor of AMSE 2021 conferences, published by IoP Science JPCS. He is the member of ISTE, CSI, IAENG, UACEE, IACSIT.
1. Generative AI: A New Frontier in Understanding and Treating
Neurodegenerative Diseases. 2. Generative AI-enhanced Diagnostic Systems:
Revolutionizing Early Disease Detection through Advanced Predictive
Analytics. 3. Obstacles and Opportunities: Generative AI in the Context of
Neurodegenerative Disorders. 4. Generative AI in the Evolution of Gene
Therapy: A Paradigm Shift in Genetic Engineering. 5. A Generative
Predictive Model for Medical Data via PCA and Iterative K-means Fusion. 6.
Exploring the Promises and Perils of Implementing Generative AI into Mental
Health Care and Emotional Well-being Support of the General Public: A
Comprehensive Overview. 7. Navigating Autism Spectrum Disorder: A Fusion of
Deep Learning and Explainable AI for Enhanced Detection and Classification.
8. Generative AI-augmented Mental Health Support: The Impact of Generative
Models on Therapeutic Practice. 9. AI and Neurodegenerative Disorders: From
Early Diagnosis to Advanced Care. 10. Prediction of Alzheimer's and
Parkinson's Diseases: AI Perspectives. 11. Advanced Fingerprint
Authentication System and Neurodegenerative Disorder Multi-modal Pattern
Recognition Techniques using Deep Learning. 12. Convolutional Neural
Network Based Biomarkers for Alzheimer's Diagnosis and Prognosis. 13.
Generative AI Novel Drug Discovery Avenues. 14. AI-driven Innovations:
Revolutionizing the Management of Neurodegenerative Disorders. 15.
Generative AI for Enhancing Cognitive Rehabilitation Patients with
Neurodegenerative Disorders.
Neurodegenerative Diseases. 2. Generative AI-enhanced Diagnostic Systems:
Revolutionizing Early Disease Detection through Advanced Predictive
Analytics. 3. Obstacles and Opportunities: Generative AI in the Context of
Neurodegenerative Disorders. 4. Generative AI in the Evolution of Gene
Therapy: A Paradigm Shift in Genetic Engineering. 5. A Generative
Predictive Model for Medical Data via PCA and Iterative K-means Fusion. 6.
Exploring the Promises and Perils of Implementing Generative AI into Mental
Health Care and Emotional Well-being Support of the General Public: A
Comprehensive Overview. 7. Navigating Autism Spectrum Disorder: A Fusion of
Deep Learning and Explainable AI for Enhanced Detection and Classification.
8. Generative AI-augmented Mental Health Support: The Impact of Generative
Models on Therapeutic Practice. 9. AI and Neurodegenerative Disorders: From
Early Diagnosis to Advanced Care. 10. Prediction of Alzheimer's and
Parkinson's Diseases: AI Perspectives. 11. Advanced Fingerprint
Authentication System and Neurodegenerative Disorder Multi-modal Pattern
Recognition Techniques using Deep Learning. 12. Convolutional Neural
Network Based Biomarkers for Alzheimer's Diagnosis and Prognosis. 13.
Generative AI Novel Drug Discovery Avenues. 14. AI-driven Innovations:
Revolutionizing the Management of Neurodegenerative Disorders. 15.
Generative AI for Enhancing Cognitive Rehabilitation Patients with
Neurodegenerative Disorders.
1. Generative AI: A New Frontier in Understanding and Treating
Neurodegenerative Diseases. 2. Generative AI-enhanced Diagnostic Systems:
Revolutionizing Early Disease Detection through Advanced Predictive
Analytics. 3. Obstacles and Opportunities: Generative AI in the Context of
Neurodegenerative Disorders. 4. Generative AI in the Evolution of Gene
Therapy: A Paradigm Shift in Genetic Engineering. 5. A Generative
Predictive Model for Medical Data via PCA and Iterative K-means Fusion. 6.
Exploring the Promises and Perils of Implementing Generative AI into Mental
Health Care and Emotional Well-being Support of the General Public: A
Comprehensive Overview. 7. Navigating Autism Spectrum Disorder: A Fusion of
Deep Learning and Explainable AI for Enhanced Detection and Classification.
8. Generative AI-augmented Mental Health Support: The Impact of Generative
Models on Therapeutic Practice. 9. AI and Neurodegenerative Disorders: From
Early Diagnosis to Advanced Care. 10. Prediction of Alzheimer's and
Parkinson's Diseases: AI Perspectives. 11. Advanced Fingerprint
Authentication System and Neurodegenerative Disorder Multi-modal Pattern
Recognition Techniques using Deep Learning. 12. Convolutional Neural
Network Based Biomarkers for Alzheimer's Diagnosis and Prognosis. 13.
Generative AI Novel Drug Discovery Avenues. 14. AI-driven Innovations:
Revolutionizing the Management of Neurodegenerative Disorders. 15.
Generative AI for Enhancing Cognitive Rehabilitation Patients with
Neurodegenerative Disorders.
Neurodegenerative Diseases. 2. Generative AI-enhanced Diagnostic Systems:
Revolutionizing Early Disease Detection through Advanced Predictive
Analytics. 3. Obstacles and Opportunities: Generative AI in the Context of
Neurodegenerative Disorders. 4. Generative AI in the Evolution of Gene
Therapy: A Paradigm Shift in Genetic Engineering. 5. A Generative
Predictive Model for Medical Data via PCA and Iterative K-means Fusion. 6.
Exploring the Promises and Perils of Implementing Generative AI into Mental
Health Care and Emotional Well-being Support of the General Public: A
Comprehensive Overview. 7. Navigating Autism Spectrum Disorder: A Fusion of
Deep Learning and Explainable AI for Enhanced Detection and Classification.
8. Generative AI-augmented Mental Health Support: The Impact of Generative
Models on Therapeutic Practice. 9. AI and Neurodegenerative Disorders: From
Early Diagnosis to Advanced Care. 10. Prediction of Alzheimer's and
Parkinson's Diseases: AI Perspectives. 11. Advanced Fingerprint
Authentication System and Neurodegenerative Disorder Multi-modal Pattern
Recognition Techniques using Deep Learning. 12. Convolutional Neural
Network Based Biomarkers for Alzheimer's Diagnosis and Prognosis. 13.
Generative AI Novel Drug Discovery Avenues. 14. AI-driven Innovations:
Revolutionizing the Management of Neurodegenerative Disorders. 15.
Generative AI for Enhancing Cognitive Rehabilitation Patients with
Neurodegenerative Disorders.







