Synopsis:

Explainable AI is currently in a rapid rise for biomedical and healthcare applications. Because of its advantages on dealing with big, complex amount of data, explainable AI concepts are applied in many fields and as a critical one, the field of medical has a remarkable interest in use of that sub-field of Artificial Intelligence. Thanks to use of machine learning, vision and Deep Learning techniques, many improvements have been done in terms of medical data analysis, diagnosis, treatment, and even personal healthcare. There are already many positive results provided by Deep Learning, in the literature of medical. For example, MIT has developed a system, which can detect breast cancer five years before its actual appearance and especially medical image analysis can be achieved with high accurateness thanks to Deep Learning. So, there is a great interest in resources focused on using Deep Learning for medical applications. Similarly explainable AI is in great demand for biomedical applications.

The main goal of the proposed edited book: ‘Biomedical data analysis and processing using Explainable (XAI) and Responsive Artificial Intelligence (RAI)’ is to inform the target audience about the most recent explaination and responsive AI driven Deep Learning and machine learning based medical applications in which only unique data gathered generally in real cases is used.

The book will be clearly distinguished from others by including chapters used only unique data, considered even negative findings (if available) and also real experiences / feedback by physicians and medical staff for use of the developed solutions. General coverage of the edited book will be as follows:

• Medical image analysis,

• Medical signal analysis,

• Medical data synthesis,

• Explainable and Responsive AI

• Deep learning

• Health care

• Biometrics security

• Drug design

• Mental disorders

• Disease diagnosis,

• Patient care and treatment,

• Genomics studies,

• Robotic-autonomous solutions,

• Medical data pre-processing.

Important Dates:

May 30, 2021: Full Chapter Submission

June 20, 2021: Accept/Reject Notification

June 30, 2021: Camera ready Submission

October 30, 2021: Final Print Version Available (Tentative)

Submission Procedure:

Chapter proposal/FULL Chapter submissions are invited from researchers and practitioners on or before May 30, 2021. Proposals should be limited to between 1000-2000 words, explaining the mission and concerns of the chapter and how it fits into the general theme of the book.

Only electronic submissions in PDF format will be considered. Please mail your proposal to aditya.khamparia88@gmail.com/drdeepakgupta.cse@gmail.com. Your submission must be made on or before the due date specified. Submissions will be reviewed in a single-blind manner.

Based on accepted chapter proposals, chapter submissions will be accepted on or before May 30, 2021. All submitted chapters will be reviewed by 3 or more reviewers. Chapter submissions must be prepared in accordance with the submission guidelines and must not exceed 25 pages (LNCS style), including bibliography and any appendix. All chapter submission must be made via email to Dr. Aditya Khamparia (aditya.khamparia88@gmail.com) and Dr. Deepak Gupta (drdeepakgupta.cse@gmail.com). Your submission must be made on or before the submission deadline and cannot be under review for any other conference, journal, or book during the entire time it is considered for the “Virtual and Augmented Reality for Automobile Industry: Innovation, Vision and Applications” book. Submissions will be reviewed in a single-blind manner.

Book Editors:

· Aditya Khamparia, Babasaheb Bhimrao Ambedkar University, Amethi, India

· Deepak Gupta, CSE Dept, Maharaja Agrasen Institute of Technology, India

· Ashish Khanna, CSE Dept, Maharaja Agrasen Institute of Technology, India

· Valentina Emilia Balas, Aurel Vlaicu University of Arad, Romania