Special Section on Machine Learning and Artificial Intelligence in Smart Healthcare: Challenges and Opportunities

Call for Papers


The goal of this Special Issue is to explore how emerging era solutions and systems in disease and healthcare applications can assist people to lead wholesome lives. In recent years, the growth of biomedical techniques brings many benefits to the protection of health. So health is a dynamic and evolving concept, influenced by changes in communities. Today, the disease prospect has shifted from infectious to chronic diseases, and the impact of nutrition, lifestyle, and environmental factors on health has become more important than ever. Healthcare computing and networking can collect and analyze full-size volumes of health-related data, leading to tremendous opportunities for the health and biomedical community. Meanwhile, these technologies have also brought new challenges and issues. In biomedical research, precision medicine is considered one of the most promising directions for healthcare development. With all these changes afoot, a better understanding of current trends in health and disease can enable appropriate planning to tackle the impending challenges facing global health care systems.

Biomedical intelligence is based on prescriptive and predictive analytics of machine learning. The healthcare computing systems include hardware, computational models, databases, and software that optimize the acquisition, transmission, processing, storage, retrieval, analysis, and interpretation of vast volumes of multi-modal health-related data. Currently, these systems have been deployed in solutions that integrate a variety of technologies, including deep learning, artificial intelligence, computer vision, Internet of Things, E-Health, bioinformatics, sensors, etc., to achieve patient-centric healthcare. The healthcare system projected that the efficiency, accuracy, predictive value, and benefits of biomedical intelligence will greatly improve in the years to come.

This Special Issue seeks research papers on current trends in health and disease, health system funding models, and novel explorations of disease pathways, including the role of nutrition, metabolism, and inflammation. We also encourage the submission of health systems and health policy-related manuscripts that focus on current health challenges and their remediation. Researchers from academic fields and industries worldwide are encouraged to submit high quality, unpublished original research articles as well as review articles in broad areas relevant to Smart Healthcare Systems.

Topics of Interest

This Special Issue encourages the submission of technical, experimental, methodological, and data analytical contributions focused on real-world problems and systems, as well as on general applications of AI and Machine Learning methodologies in medical Informatics, bioinformatics, medical and health records, and healthcare applications, including but not restricted to the following topics:

  • Disease prediction methods and techniques
  • Data mining and knowledge discovery in healthcare
  • Machine and deep learning approaches for disease and health data
  • Decision support systems for healthcare and wellbeing
  • Optimization for healthcare problems
  • Regression and forecasting for medical and/or biomedical signals
  • Healthcare information systems
  • Medical signal and image processing and techniques
  • Medical expert systems
  • Biomedical applications
  • Applications of AI techniques in healthcare and wellbeing systems
  • Machine learning-based medical systems
  • Medical data and knowledge bases
  • Neural networks in medical applications
  • Intelligent computing and platforms in medicine and healthcare
  • Biomedical text mining
  • Deep learning and methods to explain disease prediction
  • Visualization and interactive interfaces related to healthcare systems


We are soliciting original contributions that have not been published and are not currently under consideration elsewhere. Both theoretical studies and state-of-the-art practical applications are welcome. All submitted papers will be peer-reviewed and selected on the basis of their quality and relevance to the theme of this special section.

We also encourage extensions of conference papers, unless prohibited by copyright, if there is a significant difference in the technical content. Improvements such as adding a new case study or including a description of additional related studies do not satisfy this requirement. A description explaining the difference between the conference paper and the journal submission is required. The overlap between each submission and other articles, including the authors’ own papers and dissertations, should be less than 30%. Each submission must conform to the IJPE template. Please click here to submit your paper.

Special Attention

  • All submissions must be in English and in MS Word (.docx) following the IJPE template.
  • Each paper must have at least 8 pages and a maximum of 10 pages.
  • Every table and figure must have an appropriate caption.
    Each of them must be cited at least once in the paper.
  • There should be at least 10 publications in the Reference Section with every publication cited at least once.
    These publications should be listed in the order of their appearance in the submitted paper.
  • Papers that do not comply with the required format will be rejected without evaluation.

Important Dates

  • November 30, 2020
  • January 31, 2021
  • March 31, 2021
  • Paper submission
  • First round notification
  • Second round notification

Guest Editors

  • Professor Ramanathan L, Vellore Institute of Technology, Vellore, Tamilnadu, India
  • Professor Rajeshkannan R, Vellore Institute of Technology, Vellore, Tamilnadu, India
  • Professor Joan Lu, Professor, University of Huddersfield, UK

About the Guest Editors

Professor Ramanathan L
Ramanathan L has received his B.E. in Computer Science & Engineering from Bharathidasan University, Tiruchirappalli, India, and M.E in Computer Science from Sathyabama University, Chennai, India and a Ph.D. degree in Computer Science and Engineering from VIT University, Vellore, India. He is currently working as an Associate Professor in VIT, Vellore, India. His area of interest is Data Mining, Database Systems, Software Engg, Cloud Computing, and Virtualization. He has 14+ years of teaching experience. He has published papers in International Journals and Conferences. He is an Editorial board member/reviewer of International/National Journals and Conferences. His ongoing research is on Prediction, Classification, and Clustering for Educational systems. He is a member of IACSIT, CSI, ACM, IACSIT, IEEE (WIE), ACEEE.

Professor Rajeshkannan R
Rajeshkannan Regunathan has received M.Tech in Computer Science & Engineering from SASTRA University, Tanjore, and a Ph.D. degree in Computer Science and Engineering from Vellore Institute of Technology, Vellore, India. He is currently working as an Associate Professor in VIT, Vellore, India. His area of interest is Cloud Computing, Artificial Intelligence, Natural Language Processing, and Data Science. He has 13+ years of teaching experience. He has published papers in reputed International Journals and Conferences. He is a member of CSI, IEEE (WIE).

Professor Joan Lu
Joan Lu is in the Department of Computer Science and is the research group leader of Information and System Engineering (ISE) in the Centre of High Intelligent Computing (CHIC), having previously been team leader in the IT department of Charlesworth Group publishing company. She successfully led and completed two research projects in the area of XML database systems and document processing in collaboration with Beijing University. Both systems were deployed as part of company commercial productions.

She has published seven academic books and more than 200 peer reviewed academic papers. Her research publications have 1388 reads and 185 citations by international colleagues, according to incomplete statistics from the ResearchGate.

She has acted as the founder and a program chair for the International XML Technology Workshop for 11 years and serves as Chair of various international conferences. She is the founder and Editor in Chief of International Journal of Information Retrieval Research and serves as a BCS examiner of Database and Advanced Database Management Systems, and is an FHEA. She has been the UOH principle investigator for four recent EU interdisciplinary (computer science and psychology) projects: Edumecca (student responses system) (143545-LLP-NO-KA3-KA3MP), DO-IT (multilingual student response system) used by more than 15 EU countries (2009-1-NO1-LEO05-01046), and DONE-IT (mobile exam system) (511485-LLP-1-2010-NO-KA3-KA3MP), HRLAW2016 - 3090/001 - 001.

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