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Call for Papers: Using Artificial Intelligence and Machine Learning to Improve E-health and M- health

In recent years, information technologies such as Artificial Intelligence, Machine Learning have received unprecedented attention and have caused profound changes in traditional health lifestyles. In particular, these technologies had a significant impact on E-Health innovation. The ever-increasing volume of big medical data is generating new opportunities for improvement of smart E-Health and M- health. With the rapid proliferation of software and hardware technologies such as artificial technologies, mobile platform, applications and wearable devices, E-health and M- health promptly gaining ground in healthcare area Now, more intelligent experiences and algorithms are required for addressing the issues that challenge smart E-health and M-health. The SI focusses on health and biomedical applications in electronic, mobile and tablet computing, pervasive and ubiquitous computing, wearable computing and domotics. The issue will encompasses theoretical, analytical and empirical research, and comprehensive reviews of relevant research, conceptual framework and case studies of effective applications in this area. Potential topics include, but are not limited to: 1. Big data, artificial intelligence and machine Learning for E-health and M-health 2. The use of E-health and M-health 3. Diagnosis of viruses through artificial intelligence and machine Learning 4. Computational intelligence on E-health and M-health 5. Big medical data 6. Security, trust and privacy in E-health and M-health 7. E-health and M-health related software, equipment and technology

Questions regarding this Theme Issue should be directed to the Guest Editor, Prof. Sang-Bing Tsai at, or the editorial team at

How to submit 

Please submit to JMIR mHealth and uHealth by selecting 'Theme Issue 2020: Using Artificial Intelligence and Machine Learning to Improve E-health and M- health' in the "Section" drop-down list. 

See also “How do I submit to a theme issue?” in our knowledge base.