"Next-Gen Healthcare: AI-Powered Medical Diagnostics" is a comprehensive investigation into the recent and developing world that artificial intelligence assumes in medical diagnosis. The goal here is to take the reader through an in-depth analysis of the use of AI in health-foundational concepts, basic theories, and principles through real-world applications in all fields of medicine.

The book will be important for healthcare professionals, and researchers by providing an authoritative edited book on how to understand and apply AI-driven diagnostic tools and innovations. It bridges the gap between technical AI concepts and practical applications of those concepts in medical settings, giving the reader actionable insights and knowledge.

The most interesting areas that the book covers are the state-of-the-art AI methodologies concerning Explainable AI, integration of AI with IoT in healthcare, and what place could be played by quantum computing in the future. The book also describes how some ethical challenges about transparency, bias, and patient privacy should be approached and ways to overcome those challenges to make AI safely and effectively used in medical diagnostics.

This book represents a very special blend of theoretical knowledge and practical insight contributed by leading experts in the field. It acts as an important bridge between academic research and clinical application, making it a highly recommended read for all who take interest in the future of healthcare technology.

List of Topics

The contributors are expected to further the knowhow on state-of-the art research challenges, results, architecture, applications, and other achievements in (but not limited to) the following chapters and topics:

Chapters

• Natural Language Processing (NLP) in healthcare

• AI in Genomics and Precision Medicine

• AI in Remote Patient Monitoring and Telemedicine 

• AI in Mental Health Diagnostics 

• Challenges and Limitations of AI in Medical Diagnostics 

• Future Trends and Emerging Technologies

• Case Studies and Real-world Applications

Topics

• Ethical Considerations in AI for Healthcare

• Data Privacy and Security in Medical AI Applications

• Bias and Fairness in AI-driven Diagnostics

• Machine Learning for Predictive Health Analytics

• Explainable AI (XAI) in Medical Decision-Making

• Integration of AI with Internet of Medical Things (IoMT)

• Regulatory and Compliance Challenges in Medical AI

• AI in Real-time Monitoring and Emergency Response

• Quantum Computing’s Role in Future Medical AI

• Human-AI Collaboration in Clinical Settings

Submission Guidelines

a. The submitted manuscripts have not been published before and are not under consideration for publication anywhere else.

b. The initial chapter/s may be submitted in using the following format
https://drive.google.com/file/d/180Z5CSru8GY-a7hwa1Oiw1cXZYANZYCv/view?usp=sharing

or

link to guidelines

c. Prospective authors should send their manuscripts electronically through the easychair submission system as mentioned below:

https://easychair.org/conferences/?conf=nghaipmi25 or through email and include [NGHAIPMI25] in the subject email

the emails are in the end of the page.

d. There is no submission or publication fee.

e. Conference paper may be extended to be a chapter provided extension is more than 70% from the original conference paper.

f. Submitted manuscripts will be refereed by at least two independent and expert reviewers for quality, correctness, originality, and relevance before being accepted for publication.

g. Accepted manuscripts should conform to the standard guidelines of the Springer Nature. Manuscripts must be prepared using Word, and according to the guidelines link to guidelines. Manuscripts that do not follow the formatting rules will be ignored for production.

Publication

The book publication schedule is as follows:

Deadline for chapter submission: April 28, 2025

First round notification:  May 28, 2025

Camera-ready submission: June 15, 2025

Publication date: 4th quarter of 2025 /1st quarter of 2026

Contacts