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

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.