Theme Issue on Using the AI-powered cloud for COVID-19 and other infectious disease diagnosis
Fadi Al-Turjman Near East University, Nicosia, Cyprus, firstname.lastname@example.org
Ahmed E. Kamal Iowa State University, USA, email@example.com
Fabrizio Granelli University of Trento, Italy, firstname.lastname@example.org
The COVID 19 pandemic has revealed many information gaps in our understanding of the spread of contagious diseases, preventative measures and the development and deployment of vaccines.
The combination of Artificial Intelligence, machine learning, big data, cloud computing, next generation networks and mobile devices may play a role filling some of these gaps.
For example, our mobile devices might be effective in identifying symptoms and diagnosing diseases such as those COVID-19 by using accumulated cloud-based big data on disease prevelance, transmission and diagnosis. This combination effectively forms a system of distributed processing modules that can be used to record data transactions on multiple interconnected smart devices – what we call ‘an internet hospital’.
This Special Issue aims is seeking research articles that contribute to the current state of the art in cloud-assisted identification, diagnosis and management for COVID-19 and similar diseases. It aims to draw together research in mobile Internet, big data, artificial intelligence, cloud computing and other technologies that can be combined in novel ways build cost-efficient ‘internet hospitals’ and other types of medical service platforms. The challenges that internet hospitals can meet include intelligent screening, symptom monitoring, online consultation, drug distribution and mental health support. The issue aims to brings together a broad multidisciplinary community to integrate ideas, theories, models and techniques from different disciplines.
The topics of interest include, but are not limited to:
- Cloud-oriented AI for COVID-19 and similar disease diagnosis
- Big-Data and Neural Networks for tracking and disease diagnosis
- AI-driven internet hospitals and online diagnosis
- Image Progressing and ML for diagnosis
- Use cases of cloud-assisted disease detection/prevention systems
- Patient care and treatment using ML and Cloudlets enabling technologies
- Emerging cloud solutions for improved diagnosis
- Cloud-oriented ML solutions and services for medical diagnosis
- Security and privacy aspects in screening, tracking and diagnosis
Manuscript submission: 15th September 2020
Author notification: 15th November 2020
Papers must address one or more of the above issues and should be original and not be under consideration in other publication venues.
All papers will be peer reviewed by at least two independent reviewers in addition to the editors.
Extended versions of conference papers that are already published may be considered as long as the additional contribution is at least 30% new or additional content from the original.
Authors must follow the formatting and submission instructions of the Personal and Ubiuitous Computing journal at https://www.springer.com/journal/779 or see top right corner of this page.
During the first step in the submission system Editorial Manager, please select “Original article” as article type. In further steps please confirm that your submission belongs to a special issue and choose from the drop-down menu the appropriate special issue title.