Preface to Special Issue on Scientific Computing and Learning Analytics for Smart Healthcare Systems (Part II)

  • Chinmay Chakraborty Birla Institute of Technology, Mesra, Jharkhand, India
  • Sayonara Barbosa Federal University of Santa Catarina, Brazil
  • Lalit Garg University of Malta, Msida, Malta

Abstract

This special issue introduces emerging intelligent healthcare technologies that incorporate big medical data, artificial intelligence, scientific computing, federated learning, bio-inspired computation, the Internet of Medical Things, security and privacy, semantic databases, etc. Health monitoring and diagnosis for the target structure of interest are achieved through the interpretation of collected data. Advances in sensor technologies and data acquisition tools have led to a new era of big data, where massive amounts of medical data are collected by different sensors. This special issue offers valuable insights to researchers and engineers on designing intelligent bio-inspired Health 4.0 technologies and improving remote patient information delivery and care. By intelligently investigating and collecting large amounts of healthcare data (i.e., big data), sensors can enhance the decision-making process and help in early disease diagnosis. Hence, scalable machine learning, deep learning, and intelligent algorithms are needed to develop more interoperable solutions and make effective decisions in emerging sensor technologies. Optimization algorithms can be applied to acquire sensor data from multiple sources for fast and accurate health monitoring. In this special issue, seven manuscripts are published. The papers are directly or indirectly related to advanced clustering, imaging, and computing for bio-signal acquisition systems with intelligent computing.

Keywords

Smart Healthcare, intelligent healthcare technologies, big medical data, artificial intelligence, scientific computing, bio-inspired computation, the Internet of Medical Things, security and privacy, semantic databases,

References

1. R. Raman, K. Sahayaraj, M. Soni, N. Nayak, R. Govindaraj, N. Singh, Semantic web techniques for clinical topic detection in health care, Computer Assisted Methods in Engineering and Science, 31(2): 139–155, 2024, doi: 10.24423/cames.2024.493.
2. G. Geetha, J. Godwin Ponsam, K. Nimala, Noninvasive blood glucose level monitoring for predicting insulin infusion rate using multivariate data, Computer Assisted Methods in Engineering and Science, 31(2): 157–174, 2024, doi: 10.24423/cames.2024.500.
3. H. Pallathadka, S.J.R.L. Padminivalli V., M. Vasavi, P. Nancy, M. Naved, H. Kumar, S. Ray, Applicability of artificial intelligence in smart healthcare systems for automatic detection of Parkinson’s disease, Computer Assisted Methods in Engineering and Science, 31(2): 175–185, 2024, doi: 10.24423/cames.2024.557.
4. A. Victor, G. Arunkumar, R. Kannadasan, S. Rajkumar, R. Selvanambi, Survey on effective disposal of e-waste to prevent data leakage, Computer Assisted Methods in Engineering and Science, 31(2): 187–212, 2024, doi: 10.24423/cames.2024.492.
5. A. Raziq, K. Qureshi, A. Yar, K. Ghafoor, G. Jeon, Lightweight hybrid cryptography algorithm for wireless body area sensor networks using cipher technique, Computer Assisted Methods in Engineering and Science, 31(2): 213–240, 2024, doi: 10.24423/cames.2024.594.
6. J. Ramakrishna, H. Ramasangu, Classification of cognitive states using clustering-split time series framework, Computer Assisted Methods in Engineering and Science, 31(2): 241–260, 2024, doi: 10.24423/cames.2024.448.
7. Avila Clemenshia P., Deepa C., Measuring comparative statistical effectiveness of cancer subtype categorization using gene expression data, Computer Assisted Methods in Engineering and Science, 31(2): 261–272, 2024, doi: 10.24423/cames.2024.555.
Published
Jun 18, 2024
How to Cite
CHAKRABORTY, Chinmay; BARBOSA, Sayonara; GARG, Lalit. Preface to Special Issue on Scientific Computing and Learning Analytics for Smart Healthcare Systems (Part II). Computer Assisted Methods in Engineering and Science, [S.l.], v. 31, n. 2, p. 135–137, june 2024. ISSN 2956-5839. Available at: <https://cames.ippt.pan.pl/index.php/cames/article/view/1692>. Date accessed: 18 july 2024.
Section
[CLOSED]Scientific Computing and Learning Analytics for Smart Healthcare Systems