Publication will be in hardback, and as an eBook and is currently scheduled for xxxx.
Artificial Intelligence (AI) in general and machine learning (ML) and deep learning (DL) in particular and related digital technologies are a couple of fledging paradigms that the next generation healthcare services are sprouting towards. These digital technologies can transform various aspects of healthcare, leveraging advances in computing and communication power. With a new spectrum of business opportunities, AI-powered healthcare services would improve the lives of patients, their families, and societies. However, the application of AI in the healthcare field requires special attention given the direct implication with human life and well-being. Rapid progress in AI leads to the possibility of exploiting healthcare data for designing practical tools for automated diagnosis of chronic diseases such as dementia and diabetes.
Data is the fuel for any AI application. In the medical domain, on the other hand, data can be challenging to obtain, mainly for privacy concerns. That makes the combination of both AI and healthcare a significant research challenge.
In this book, we aim to highlight the current research trends in applying AI models in various disease diagnoses and prognoses to provide enhanced healthcare solutions.
We particularly encourage submissions of state of the art and tutorial-based articles.
Topics of interest include, but are not limited to: Artificial Intelligence for:
Disease detection
Reducing human errors in medical treatment
Healthcare ( with focus on Machine learning and deep learning techniques)
Reducing medical misdiagnosis errors
Cancer scanning
Managing long term conditions such as Alzheimer's and Parkinson's disease
Medical Imaging and cell biology
Guided robots for medical care
Surgery and Intervention
Precision medicine informatics
Therapeutics
Electronic health records and clinical knowledge management
Mental health adaptive tools and apps
Follow-up of post-discharge patients
Public health surveillance
Ethical implications of using AI in healthcare
Convergence and standardisation issues for AI in healthcare
Security and privacy features for AI in healthcare
For the first draft, there is no page limit and no specific file template to follow.
Chapters should be submitted in word or pdf format to the following email address: cfp4bookandconf@gmail.com
Chapter proposal/abstract submission: xxxxxx
Notification of initial acceptance: September, 30th, 2021
Chapter Submission: xxxxxxxx
Feedback/Review on chapters: xxxxxx
Final Chapter Submission: xxxxx
Book chapters will be peer-reviewed and the following criteria will be applied for the selection process.
· Quality of contribution in terms of novelty, structure and clarity
· The chapters should be self-contained and written in a tutorial-based format.
· Comparison with related work should be included
· Case studies should highlight the 'generic' lessons learned to be applied in similar projects
· Contributions should address a topic related to the application of AI in healthcare.
· Survey papers are also welcome
Once your chapter has been accepted, please use the Latex template found here to format your paper.
The edited book will be published by CRC Press.
Dr. Ghita Kouadri Mostefaoui
Department of Computer Science
University College London
Gower Street 66-72, London WC1E 6BT
United Kingdom
Email: cfp4bookandconf@gmail.com
Dr. Faisal Tariq
James Watt School of Engineering
University of Glasgow
72 Oakfield Avenue
United Kingdom
Email: Faisal.Tariq@glasgow.ac.uk
Latest information about the Call for Papers can be found here: https://sites.google.com/view/crc-book (this page).