Call for Chapters: AI-Driven Breakthroughs in Antimicrobial Resistance

Editors

Hemachandran Kannan, Professor, School of Business, Woxsen University, India
Raul Rodriguez, Vice President, Woxsen University, Hyderabad, India, India
Sivaramakrishnan Rajaraman, Research Scientist, Computational Health Research Branch, National Library of Medicine, National Institutes of Health, USA, United States
Anil Pise, Siatik Premier Google Cloud Platform Partner Johannesburg South Africa, University of the Witwatersrand Johannesburg-South Africa Computer Science, South Africa

Call for Chapters

Proposals Submission Deadline: June 30, 2024
Full Chapters Due: September 22, 2024
Submission Date: September 22, 2024

Introduction

Antimicrobial resistance (AMR) poses a significant threat to global health, potentially leading to a post-antibiotic era where common infections become deadly. "AI-Driven Breakthroughs in Antimicrobial Resistance" explores how artificial intelligence (AI) is transforming the fight against AMR. This book delves into AI's role in discovering new antibiotics, understanding resistance mechanisms, and designing effective treatments. Through case studies, expert interviews, and comprehensive reviews, we highlight AI's ability to accelerate drug discovery, optimize therapies, and personalize patient care. Additionally, we address the ethical, social, and policy implications of integrating AI into antimicrobial research, emphasizing the need for equitable access and interdisciplinary collaboration. "AI-Driven Breakthroughs in Antimicrobial Resistance" aims to inspire innovation and foster a collaborative approach to combating AMR, showcasing AI's potential to revolutionize infectious disease treatment and safeguard global health.

Objective

"AI-Driven Breakthroughs in Antimicrobial Resistance" aims to demonstrate how artificial intelligence (AI) can revolutionize the fight against antimicrobial resistance (AMR). By showcasing cutting-edge AI methodologies and successful applications, the book seeks to inspire innovation and cross-disciplinary collaboration among researchers, healthcare professionals, and policymakers. It provides a comprehensive resource on AI's role in drug discovery, understanding resistance mechanisms, and optimizing treatments. Additionally, the book addresses ethical considerations and the need for equitable access to AI-driven healthcare solutions, contributing to policy-making and advancing global health research against AMR.

Target Audience

"AI-Driven Breakthroughs in Antimicrobial Resistance" is geared towards a diverse and interdisciplinary audience, including biomedical researchers and scientists interested in AI methodologies for drug discovery and disease understanding, healthcare professionals and clinical practitioners seeking insights into emerging technologies influencing treatment protocols and patient care, and public health officials and policymakers needing to understand AI's potential in informing public health strategies and antimicrobial stewardship. Additionally, AI and data science professionals looking to apply their skills to healthcare and drug discovery challenges, students and academics across medicine, pharmacology, computer science, and public health fields, as well as general readers with an interest in science, technology, and healthcare innovation, will benefit from the book's comprehensive insights into AI's transformative role in combating AMR.

Recommended Topics

Chapters 1. Introduction to Antimicrobial Resistance: A Modern Plague 2. The Rise of AI in Healthcare: Transforming Medicine's Future 3. Decoding AMR: AI's Role in Understanding Pathogen Evolution 4. AI in Drug Discovery: Pioneering the Search for New Antibiotics 5. Predictive Analytics and AMR: Forecasting Outbreaks and Resistance Trends 6. Personalized Medicine and AMR: AI's Impact on Treatment Efficacy 7. Combating AMR with Machine Learning: Case Studies and Success Stories 8. Generative AI in Antimicrobial Research: Beyond Traditional Boundaries 9. Data-Driven Strategies for Infection Control and Prevention 10. The Ethical Implications of AI in AMR Research 11. Lab to Clinic: The Journey of AI-Enabled Antimicrobials 12. The Global Fight Against AMR: AI's Role in International Collaboration 13. Future Directions: AI, AMR, and Beyond 14. Navigating the Challenges: Funding, Infrastructure, and Workforce for AI in AMR 15. Case Studies

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 22, 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 Breakthroughs in Antimicrobial Resistance. 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 22, 2024: Full Chapter Submission
November 3, 2024: Review Results Returned
December 1, 2024: Final Acceptance Notification
December 8, 2024: Final Chapter Submission



Inquiries

Hemachandran Kannan Professor, School of Business, Woxsen University hemachandran.k@woxsen.edu.in Raul Rodriguez Vice President, Woxsen University, Hyderabad, India raul.rodriguez@woxsen.edu.in Sivaramakrishnan Rajaraman Research Scientist, Computational Health Research Branch, National Library of Medicine, National Institutes of Health, USA raaju.shiv1@gmail.com Anil Pise Siatik Premier Google Cloud Platform Partner Johannesburg South Africa, University of the Witwatersrand Johannesburg-South Africa Computer Science anil.pise7@gmail.com

Classifications


Computer Science and Information Technology; Life Sciences; Medicine and Healthcare; Social Sciences and Humanities; Physical Sciences and Engineering
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