Important Submission Information
– deadline for submissions: Extended deadline July 15, 2019
– first decision (accept/reject/revise, tentative): September 15, 2019
– submission of revised papers: November 15, 2019
– notification of final decision (tentative): January 15, 2020
– journal publication (tentative): first half of 2020
Lia Morra, Politecnico di Torino, Italy
Valentina Gatteschi, Politecnico di Torino, Italy
Saraju Mohanty, University of North Texas, USA
Corresponding TETC Editor:
Yuan-Hao Chang, IIS, Academia Sinica, Taipei, Taiwan
Authors are invited to submit a manuscript to this special section. Relevant topics of interest must fall in the domain of e-Health to m-Health and p-Health (*-Health) and include (but are not limited to):
1. Emerging applications in next-generation healthcare systems
2. Computing aspects of pervasive and ubiquitous healthcare systems
3. Technologies, methods and applications empowering data management and sharing, user privacy,
security and safety (e.g. blockchain, privacy by design, fault tolerance, etc.)
4. Assistive computing technologies for children, elderly and disabled individuals
5. Technological advances (e.g. gamification, IoT, mixed/augmented reality, artificial intelligence) for wellness/well-being management
6. Non-conventional and emerging applications of data analytics and machine learning
7. Applications and methodologies leveraging web-generated Data for healthcare and digital epidemiology
8. Semantic Computing applications and methods
Submitted papers must include new significant research-based technical contributions in the scope of the journal. Purely theoretical, technological or lacking methodological-and-generality papers are not suitable to this special issue. The submissions must include clear evaluations of the proposed solutions (based on simulation and/or implementations results) and comparisons to state-of-the-art solutions. For additional information please contact the Guest Editors by sending an email exclusively to email@example.com. Papers under review elsewhere are not acceptable for submission. Extended versions of published conference papers (to be included as part of the submission together with a summary of differences) are welcome but there must have at least 50% of new impacting technical/scientific material in the submitted journal version and there should be less than 30% verbatim similarity level as reported by a tool (such as CrossRef).
Guidelines concerning the submission process, LaTeX and Word templates can be found here. While submitting through ScholarOne, at https://mc.manuscriptcentral.com/tetc-cs, please select the option “Special Section on New Frontiers in Computing for Next-Generation Healthcare Systems.
As per TETC policies, only full-length papers (10-16 pages with technical material, double column – papers beyond 12 pages will be subject to MOPC, as per CS policies) can be submitted to special sections. The bibliography should not exceed 45 items and each author’s bio should not exceed 150 words.
A profound transformation is revolutionizing the healthcare system powered by technological advances in computing and information sciences. The pervasiveness of mobile devices, wearable sensors, smart devices, social media, etc., on one hand, and fast-paced advances in data analytics, artificial intelligence, machine learning and edge computing, on the other hand, bring unprecedented opportunities to deliver patient-centered, personalized healthcare in the patients’ environment. The rising importance of the eHealth, m-Health (mobile Health) and p-Health (pervasive Health) paradigms are shifting the healthcare provision model from a centralized, standardized, hospital-centered, episodic model, to a decentralized, home-based, personalized, patient-centered and continuous paradigm, pushing the boundary of traditional Health Informatics systems and applications.
From a societal point of view, new opportunities arise for improving the life of a child, elderly, disabled individuals, and those suffering from chronic illnesses, as well as for the prevention of the current epidemics of lifestyle-related diseases. In the future, individuals and patients will use a number of devices measuring a multitude of different signals. The pervasive nature of modern technologies is pushing society to embrace a broader definition of healthcare management, from disease to wellness management, empowering people to take charge of their own health and well-being. At the same time, emerging technologies and data-driven processes are expected to reduce the social and monetary costs of healthcare systems, which have been rising steadily for the past 20 years.
Research and public health are also set to increasingly benefit from the enormous quantities of data available through social media, social networks and the Internet-of-Things. Healthcare Big Data have great potential to empower researchers, industry and practitioners with novel insights, hypothesis and applications, leveraging biological and personal data seamlessly collected in unprecedented real-life scenarios. As an example, the emerging field of Digital Epidemiology is beginning to leverage digital data, usually collected for other purposes, to enhance our understanding of diseases and infections, e.g. by connecting the study of social networks to the modeling of epidemics and infectious diseases. However, the full potential of data collected outside of the traditional structured methodologies of biomedical research and healthcare informatics is still largely untapped.
With technological advances come new opportunities, but also new challenges and threats. Issues related to information security, patients’ privacy and data ownership are increasingly pushed into the spotlight. In this respect, emerging technologies such as blockchain provide new ways to record patient’s data, written by multiple parties/devices, and make them available to the different actors involved in healthcare provision. There is relative little experience yet on the quality, reliability and biases in healthcare data generated from the Web and social network sites. Data analytics could be used against individuals, who could suffer discrimination based on their health status, if the latter can be inferred by online data traces. This special issue aims to present the technological advancements in computing that are underpinning the current revolution in healthcare, shaping our future concept of health management in the broadest sense of the term. Cross-disciplinary and emerging applications that lay at the intersection of different sub-fields are especially welcome.
Guest Editor Bios
Lia Morra (M18) received the MSc and the PhD degrees in computer engineering from Politecnico di Torino in 2002 and 2006, respectively. Currently, she is post-doctoral Associate at the Department of Control and Computer Engineering of Politecnico di Torino, Italy. From 2006 to 2016 she joined im3D, where she served as Chief Scientific Officer from 2014 to 2017; she guided the team developing the core medical image analysis and artificial intelligence technology components from design to regulatory approval. Her research interests include computer vision, pattern recognition, machine learning and computer-assisted
medical image interpretation. She has authored numerous papers in international journals and conferences, and was awarded three patents. She is a member of IEEE, and served as a member of the AAPM Computer Aided Image Analysis Subcommittee. Further information available at https://liamorra.wordpress.com.
Valentina Gatteschi (M19) received her B.Sc. and M.Sc. degrees in management engineering and the Ph.D. degree in computer engineering in 2005, 2008 and 2013, respectively. She currently is an Assistant Professor with time contract at the Department of Control and Computer Engineering of Politecnico di Torino, Italy. Her main interests are natural language processing, human-computer interaction, intelligent systems and blockchain. She has authored numerous papers in international journals and conferences. She has been involved in a number of European projects. She has been an invited speaker at several conferences/workshops on blockchain and is currently serving as a member of the IEEE Blockchain Education Subcommittee. Further information available at
Saraju P. Mohanty (M99, SM08) is a Professor at the University of North Texas. His research is in “Smart Electronic Systems” which has been funded by National Science Foundations, Semiconductor Research Corporation, US Air Force, IUSSTF, and Mission Innovation. He has authored 280 research articles, 3 books, and invented 4 US patents. His Google Scholar h-index is 29 and i10-index is 90. He has received 4 best paper awards and has delivered multiple keynote talks at various International Conferences. He received IEEE-CS-TCVLSI Distinguished Leadership Award in 2018 for services to the IEEE, and to the VLSI research community. He has been recognized as a IEEE Distinguished Lecturer by the Consumer Electronics Society (CESoc) since 2017. He was conferred the Glorious India Award in 2017 for his exemplary contributions to the discipline. He received Society for Technical Communication (STC) 2017 Award of Merit for his outstanding contributions to IEEE Consumer Electronics Magazine. He was the recipient of 2016 PROSE Award for best Textbook in Physical Sciences & Mathematics from the Association of American Publishers for his Mixed-Signal System Design book published by McGraw-Hill in 2015. He was conferred 2016-17 UNT Toulouse Scholars Award for sustained excellent scholarship and teaching achievements. He is the Editor-in-Chief (EiC) of the IEEE Consumer Electronics Magazine (CEM). He served as the Chair of Technical Committee on VLSI, IEEE Computer Society during 2014-2018. Further information available at https://www.smohanty.org.