Transformation of Healthcare: From e-Health to Digital Health

This special session is organized and supported by Artificial Intelligence & Data Analytics (AIDA) Research Lab, Prince Sultan University, Riyadh, Saudi Arabia

Session Chair:

Prof. Dr.Tanzila Saba, Research Professor, AIDA Lab, Prince Sultan University, Riyadh, Saudi Arabia

Session Co-chairs:

  • Dr. Rehman Khan, Senior Researcher, AIDA Lab, Prince Sultan University, Riyadh, Saudi Arabia
  • Dr.Khalid Haseeb, Peshawar, Pakistan Computer Science Department, Islamia College (Chartered University)
  • Dr.Hoshang Kolivand, Liverpool John Moores University, Liverpool, United Kingdom

Synopsis:

Health informatics has become an area of interest among the researchers from diverse fields due to the multidisciplinary domain. Applications of IoT, AI and Big Data technologies are booming and will continue to grow exponentially in the coming years and decades. The new technologies find their way into every aspect of our lives, and appear in a multitude of forms and applications. Recently, the transition from e-health to digital health advanced the diversity of applications, innovations and other specialties

The health sector has also taken an active part in emerging technology adoptions and has facilitated the development of public health over the last few years. The digitization of society, and hence of the healthcare system, relies on the internet, the connectivity of basic services and terminology such as e-Health, healthcare information, telemedicine, teleheath and m-Health. Such terms have been used to describe the application of ICT to health care, clinical guidelines, experts’ discussion and counseling.

The positive impact of technology in healthcare is the digital revolution of healthcare. Artificial intelligence-enabled medical devices, telemedicine, and electronic health records are a few solid examples of digital transformation in healthcare The World Health Organization has stated: Moving from e-Health to Digital Health puts more emphasis on digital consumers, with a wider range of smart-devices and connected equipment being used, together with other innovative and evolving concepts as that of Internet of things (IoTs) and the more widespread use of artificial intelligence (AI), big data and analytics. Digital Health is changing the way health systems are run and health care is delivered. Digital transformation is the key to elevate healthcare to the next level in terms of security, cost-efficiency, and success rates while concurrently apprehending the potential of e-health and digital health systems.

The goal of the track is to provide a forum for researchers and health practitioners to share their research findings, innovative approaches, currents challenges, and real-time case studies of digital health care transformation, as well the novel expected future applications of Artificial Intelligence in the transformation of healthcare from e-health to digital health.

Topics:

The special issue seeks to include original, high-quality contributions to AI systems in healthcare. The key areas of concern include but are not limited to:

  • AI methodologies for medical data analysis

  • AI and big data analytics application in medical domain

  • Administrative data analysis using AI techniques

  • Medical data acquisition, cleaning and integration using AI methodologies

  • Medical image recognition using AI technologies

  • Natural language processing in medical documents

  • Applications of AI Healthcare Information Technology

  • Intelligent Assistance and Diagnosis

  • Effective Telemedicine security Techniques

  • Knowledge Management of Medical Data

  • Data Mining and Knowledge Discovery in Medicine

  • Personal medical feature data

  • Medical device technologies

  • Machine Learning-based Medical Systems

  • Pattern Recognition in Medicine

  • Ambient Intelligence and Pervasive Computing in Medicine and Health Care

  • VR/AR in medical education, diagnosis and surgery

  • Data governance and data security in digital health

  • Theories, models and classification frameworks of digital health

 

Paper Submission:

Prospective authors are invited to submit full-length papers (not exceeding 6 pages) conform to the IEEE format . All papers will be handled and processed electronically via the EDAS online submission system.