Call for Chapters: Deep Generative Models for Integrative Analysis of Alzheimer's Biomarkers

Editors

Abhishek Kumar, Associate Professor ,Chandigarh University, India
Rakesh Sakthivel, Assistant Professor, GITAM University, Bengaluru, India
Gayathri Nagasubramanian, Assistant Professor, GITAM (Deemed to be University), India
Srivel Ravi, Assistant Profesor in Dept of CSE Adhiparasakthi Engineering College Melmaruvathur, India
Dhaya Chinnathambi, Profesor in Dept of CSE Adhiparasakthi Engineering College Melmaruvathur, India

Call for Chapters

Proposals Submission Deadline: May 19, 2024
Full Chapters Due: July 21, 2024
Submission Date: July 21, 2024

Introduction

Deep Generative Models for Integrative Analysis of Alzheimer's Biomarkers" delves into the intersection of cutting-edge technology and critical medical research. In this groundbreaking work, the intricate relationship between deep generative models and Alzheimer's disease biomarkers is explored with precision. Through a synthesis of advanced machine learning algorithms and comprehensive neuroscientific data, this book offers a pioneering approach to understanding the complexities of Alzheimer's progression. From uncovering novel biomarkers to predicting disease trajectories, the integration of deep generative models revolutionises our capacity to analyse and interpret Alzheimer's-related data. With a blend of technical expertise and medical insight, this text serves as a beacon for researchers, clinicians, and technologists alike, shaping the future of Alzheimer's research and diagnosis.

Objective

The objective of "Deep Generative Models for Integrative Analysis of Alzheimer's Biomarkers" is to explore the application of advanced deep generative models in comprehensively analyzing Alzheimer's disease biomarkers. Through this exploration, the book aims to provide insights into novel biomarkers, disease progression predictions, and ultimately contribute to the advancement of Alzheimer's research and diagnosis through innovative computational techniques.

Target Audience

The book "Deep Generative Models for Integrative Analysis of Alzheimer's Biomarkers" targets a diverse audience including researchers, scientists, and practitioners in the fields of machine learning, artificial intelligence, neuroscience, and Alzheimer's disease research. Additionally, clinicians, healthcare professionals, and individuals involved in medical diagnostics and treatment strategies will find valuable insights in this book.

Recommended Topics

Introduction to Alzheimer's disease and biomarkers Fundamentals of deep generative models Integration of multi-modal Alzheimer's biomarker data Novel approaches for feature extraction and representation learning Predictive modeling of Alzheimer's disease progression Interpretability and visualization techniques for model insights Clinical implications and applications of deep generative models Ethical considerations and challenges in Alzheimer's biomarker analysis Future directions and emerging trends in integrative analysis Case studies and real-world applications of deep generative models in Alzheimer's research

Submission Procedure

Researchers and practitioners are invited to submit on or before May 19, 2024, a chapter proposal of 1,000 to 2,000 words clearly explaining the mission and concerns of his or her proposed chapter. Authors will be notified by June 2, 2024 about the status of their proposals and sent chapter guidelines.Full chapters are expected to be submitted by July 21, 2024, and all interested authors must consult the guidelines for manuscript submissions at https://www.igi-global.com/publish/contributor-resources/before-you-write/ prior to submission. All submitted chapters will be reviewed on a double-blind review basis. Contributors may also be requested to serve as reviewers for this project.

Note: There are no submission or acceptance fees for manuscripts submitted to this book publication, Deep Generative Models for Integrative Analysis of Alzheimer's Biomarkers. All manuscripts are accepted based on a double-blind peer review editorial process.

All proposals should be submitted through the eEditorial Discovery® online submission manager.



Publisher

This book is scheduled to be published by IGI Global (formerly Idea Group Inc.), an international academic publisher of the "Information Science Reference" (formerly Idea Group Reference), "Medical Information Science Reference," "Business Science Reference," and "Engineering Science Reference" imprints. IGI Global specializes in publishing reference books, scholarly journals, and electronic databases featuring academic research on a variety of innovative topic areas including, but not limited to, education, social science, medicine and healthcare, business and management, information science and technology, engineering, public administration, library and information science, media and communication studies, and environmental science. For additional information regarding the publisher, please visit https://www.igi-global.com. This publication is anticipated to be released in 2025.



Important Dates

May 19, 2024: Proposal Submission Deadline
June 2, 2024: Notification of Acceptance
July 21, 2024: Full Chapter Submission
August 25, 2024: Review Results Returned
September 22, 2024: Final Acceptance Notification
September 29, 2024: Final Chapter Submission



Inquiries

Abhishek Kumar,
Associate Professor ,Chandigarh University
abhishekkmr812@gmail.com

Rakesh Sakthivel
Assistant Professor, GITAM University, Bengaluru
rakesherme@gmail.com

Gayathri Nagasubramanian
Assistant Professor, GITAM (Deemed to be University)
gayathrierme@gmail.com

Srivel Ravi
Assistant Professor in Dept of CSE Adhiparasakthi Engineering College Melmaruvathur
rsrivel@gmail.com

Dhaya Chinnathambi
Professor in Dept of CSE Adhiparasakthi Engineering College Melmaruvathur
dhaya.c@gmail.com



Classifications


Computer Science and Information Technology; Security and Forensics; Science and Engineering
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