Digital Transformation in Healthcare

This book presents a collection of papers revealing the impact of advanced computation and instrumentation on healthcare. It highlights the increasing global trend driving innovation for a new era of multifunctional technologies for personalized digital healthcare. Moreover, it highlights that contemporary research on healthcare is performed on a multidisciplinary basis comprising computational engineering, biomedicine, biomedical engineering, electronic engineering, and automation engineering, among other areas

Experimental Evaluation of Growing and Pruning Hyper Basis Function Neural Networks Trained with Extended Information Filter

In this paper we test Extended Information Filter (EIF) for sequential training of Hyper Basis Function Neural Networks with growing and pruning ability (HBF-GP). The HBF neuron allows different scaling of input dimensions to provide better generalization property when dealing with complex nonlinear problems in engineering practice. The main intuition behind HBF is in generalization of Gaussian type of neuron that applies Mahalanobis-like distance as a distance metrics between input training sample and prototype vector. We exploit concept of neuron’s significance and allow growing and pruning of HBF neurons during sequential learning process. From engineer’s perspective, EIF is attractive for training of neural networks because it allows a designer to have scarce initial knowledge of the system/problem. Extensive experimental study shows that HBF neural network trained with EIF achieves same prediction error and compactness of network topology when compared to EKF, but without the need to know initial state uncertainty, which is its main advantage over EKF

How digital data are used in the domain of health: A short review of current knowledge

In the era of digitalization, digital data is available about every aspect of our daily lives, including our physical and mental health. Digital data has been applied in the domain of healthcare for the detection of an outbreak of infectious diseases, clinical decision support, personalized care, and genomics. This paper will serve as a review of the rapidly evolving field of digital health. More specifically, we will discuss (1) big data and physical health, (2) big data and mental health, (3) digital contact tracing during the COVID-19 pandemic, and finally, (4) ethical issues with using digital data for health-related purposes. With this review, we aim to stimulate a public debate on the appropriate usage of digital data in the health sector

Impact of New Method for Laying Separate Sewer System on Pavement Layers

The method of installing underground infrastructure has a significant influence on road resistance and performance under live loads such as traffic. This research presents a new method for laying separate sewer systems by using one trench to sit both sanitary pipe and storm pipe and considers the effects of this approach on the pavement strength. Experimental tests have been conducted in the laboratory using a trench 2.5x0.45x1 metre to install two pipes one over the other (sanitary pipe in the bottom and storm pipe on top). Two cases have tested, the first case using 5 cm surface layer of cold mix asphalt while the second is using soil. A series of loads were applied to test the behaviour of this new system and its effects on the pavement surface layer and the buried pipe. The comparison between the rut print of the live load on the soil layer and the pavement layer was conducted. Results demonstrated that using the cold mix asphalt is still insufficient to provide enough safety to protect buried pipe as a reason of needing to relatively long time to acquire high stiffness. Therefore, minimum cover depth to protect pipelines still required