Call for Papers on Scientific Computing and Learning Analytics for Smart Healthcare Systems


Theme. This special issue introduces the emerging intelligent technologies in healthcare, which deploy big medical data, artificial intelligence, cloud/fog scientific computing, federated learning, bio-inspired computation, Internet of medical things, wireless technologies, 5G and beyond, security and privacy, semantic database, content-based image retrieval, augmented/virtual/mixed reality, etc. The health monitoring and diagnosis for the target structure of interest are achieved through the interpretation of collected data. The advances in sensor technologies and data acquisition tools have led to the new era of big data, where massive medical data are collected by different sensors.

This special issue will also offer valuable perceptions to researchers and engineers on how to design intelligent bio-inspired Health 4.0 technologies and improve patient information delivery care remotely. The sensors generated patient-centric data can be processed through the next-generation cellular systems. This large volume of data, often called big data, cannot readily be processed by traditional data processing algorithms and applications. By intelligently investigating and collecting large amounts of healthcare data (i.e., big data), the sensor can enhance the decision-making process and early disease diagnosis. Hence, there is a need for scalable machine learning, deep learning, and intelligent algorithms that lead to more interoperable solutions and make effective decisions in emerging sensor technologies.

This continuous and exponential growth is facilitated by investments and research activities originating from industry, academia, and governments, while the penetration of these technologies is also driven by the high technology acceptance rates of both consumers and technologists across disciplines. Such networks collect, store, and exchange a large volume of heterogeneous data specifically for the healthcare domain. Pervasive healthcare, as a relevant application domain in this context, aims to revolutionize the delivery of medical services through a medical assistive environment and facilitate patients’ independent living . The optimization algorithms can be applied because of acquiring the sensor data from multiple sources for fast and accurate health monitoring.

We welcome contributions to the intelligent biomedical data acquisition and processing topics that support prospective healthcare applications. We also invite research that discusses the life cycle of sensor devices and protocols with the help of energy-aware design, production, and utilization, as well as the Internet of Things technologies such as tags, sensors, sensing networks, and internet technologies.

We seek original and high-quality submissions on, but not limited to, one or more of the following topics:

  • Wireless body area sensor networks for bio-inspired health 4.0
  • Scientific computing for Healthcare Cyber-Physical Systems
  • Decision-Making Unit (DMU) for health 4.0
  • 5G and beyond for healthcare
  • Recent trends in sensor technology and wearable scientific computing
  • Sensors for the Internet of Things
  • Healthcare sensor data analytics
  • Wireless and wearable sensors for bio-inspired health informatics
  • Cloud scientific computing and big data technologies for sensor data processing
  • Complex sensors data handling
  • Internet of Things health systems for next-generation networks
  • Remote human’s health and activities monitoring
  • Smart sensors technologies for healthcare
  • Big medical data analytics
  • Optimal sensors establishment algorithms
  • Mobility enhancement of sensors data streams
  • Advances of data acquisition to data fusion
  • Decision-making systems for sensors data
  • Artificial intelligence for health informatics
  • Data mining and fusion algorithms for Wireless Body Area Networks (WBAN)
  • Health sensor data management
  • Sensor informatics for homecare monitoring
  • Sensors for VR/AR, mixed reality, and data visualization


Manuscript preparation and submission

Computer Assisted Methods in Engineering and Science (CAMES) is a refereed international journal published quarterly and indexed by Scopus and EBSCO databases.

All manuscripts must be submitted through the journal website:

Submission must be clearly marked in the system as “Scientific Computing and Learning Analytics for Smart Healthcare Systems”. The publication in this Special Issue is free of charge for the Authors, and the published manuscript will be freely available for the Readers through the Journal website (

 Important dates:

Deadline for full-length paper submission: April 30, 2022
Notification of the reviewers’ first feedback: May 30, 2022
Deadline for the revised version submission: June 30, 2022
Announcement of acceptance by Guest Editors: July 30, 2022
Deadline for the final manuscript submission: August 29, 2022

Guest Editors:

Dr. Chinmay Chakraborty, Electronics & Communication Engineering, Birla Institute of Technology, Mesra, India

Dr. Lalit Garg, Information & Communication Technology Department, University of Malta, Msida, Malta

Dr. Sayonara F.F. Barbosa, Department of Nursing and Graduate Program in Health Informatics, Federal University of Santa Catarina, Florianópolis, Brazil

Prof. Michał Kleiber
– Past ECCOMAS President, Institute of Fundamental Technological Research, Warsaw, Poland

Prof. Tadeusz Burczyński
– Chairman of TC on Computational Solids & Structural Mechanics of ECCOMAS, Director of the Institute of Fundamental Technological Research, Warsaw, Poland