Call for Chapters: AI-Driven Innovation in Healthcare Data Analytics

Editors

Leyla Özgür Polat, Pamukkale University, Turkey
Olcay Polat, Pamukkale University, Turkey

Call for Chapters

Proposals Submission Deadline: June 30, 2024
Full Chapters Due: September 1, 2024
Submission Date: September 1, 2024

Introduction

The rapid advancement of artificial intelligence (AI) technologies has ushered in a transformative era in healthcare, where data-driven insights are increasingly becoming pivotal in shaping patient care, operational efficiency, and strategic decision-making. The convergence of AI with healthcare data analytics represents a groundbreaking frontier, promising to address complex challenges and catalyze innovation across the healthcare spectrum. AI-driven techniques such as machine learning (ML), deep learning, and data mining are redefining the capabilities of healthcare data analytics. These technologies enable the extraction of valuable insights from vast and complex datasets, ranging from electronic health records (EHRs) and genomic data to real-time patient monitoring systems and population health databases. By harnessing the power of AI, healthcare professionals can make more informed decisions, predict patient outcomes with greater accuracy, and optimize resource allocation to enhance the overall quality of care.

Objective

This book, "AI-Driven Innovation in Healthcare Data Analytics," provides a comprehensive exploration of the myriad ways in which AI is being applied to revolutionize healthcare management. Through a blend of theoretical frameworks, well-konwn data sets, practical applications, and real-world case studies, the volume delves into key topics such as predictive modeling, clinical decision support systems, and the optimization of healthcare operations. It also addresses the ethical and privacy considerations inherent in the use of AI in healthcare, ensuring a balanced perspective on the potential and challenges of these technologies. The publication aims to have a profound impact on the research community by advancing the understanding of AI-driven innovations in healthcare. By showcasing state-of-the-art strategies and applications, the book aspires to inspire researchers to pursue new avenues of inquiry and to innovate within their respective fields. Additionally, the interdisciplinary nature of the content fosters collaboration among healthcare management, data science, and engineering disciplines, promoting a holistic approach to solving healthcare challenges. Real-world case studies and well-konwn data sets featured in the book illustrate the transformative potential of AI in healthcare settings. From enhancing patient engagement through AI-powered platforms to enabling personalized treatment plans using genomic data, these examples highlight the practical benefits of integrating AI into healthcare processes. Furthermore, the book explores how AI can optimize operational efficiency, whether through predictive analytics for patient outcome forecasts or the detection of fraudulent activities in revenue cycle management.

Target Audience

This book is intended for researchers, practitioners, and students across a broad spectrum of disciplines, including industrial engineering, computer science, healthcare management, and data science. It will serve as a valuable resource for academics seeking to deepen their knowledge of AI-driven approaches in healthcare data analytics and management. Practitioners working in healthcare organizations will find practical insights and case studies that can inform decision-making processes and drive organizational improvements. Additionally, graduate students and professionals aiming to explore the latest advancements in AI-driven healthcare analytics will benefit from the diverse perspectives presented in this book.

Recommended Topics

- Introduction to AI and machine learning in healthcare - Data mining and business intelligence in healthcare - Collecting, integrating, and preparing healthcare data - Standardizing and ensuring quality of healthcare datasets - Predictive modeling for patient outcome forecasts - Clinical decision support systems using AI and ML - Optimizing healthcare operations with AI algorithms - Using simulation for operational efficiency - Analyzing population health trends with AI - Detecting fraud and anomalies with AI - AI for revenue cycle management in healthcare - Developing AI-powered patient engagement platforms - Remote patient monitoring with wearables and IoT - Personalizing treatment using AI and genomics - Evaluating healthcare quality with AI - Ethical and privacy considerations in AI healthcare - Case studies of AI in healthcare - Emerging trends in healthcare AI

Submission Procedure

Researchers and practitioners are invited to submit on or before June 30, 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 July 14, 2024 about the status of their proposals and sent chapter guidelines.Full chapters are expected to be submitted by September 1, 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-anonymized 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, AI-Driven Innovation in Healthcare Data Analytics. All manuscripts are accepted based on a double-anonymized 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

June 30, 2024: Proposal Submission Deadline
July 14, 2024: Notification of Acceptance
September 1, 2024: Full Chapter Submission
October 6, 2024: Review Results Returned
November 3, 2024: Final Acceptance Notification
November 10, 2024: Final Chapter Submission



Inquiries

Leyla Özgür Polat Pamukkale University lozgur@pau.edu.tr Olcay Polat Pamukkale University olcaay@gmail.com

Classifications


Business and Management; Computer Science and Information Technology; Education; Medicine and Healthcare; Social Sciences and Humanities; Physical Sciences and Engineering
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