Special issue: Bio-sense Information Systems

Trends that start out small can wind up transforming the way we live. Bio-sense information systems seemed like a fad for us. Today we use it for many formation systems and more with people. Bio-sense Information Systems are related biological feature processing for biomedical (Fan et al. 2020), bio-inspired (Liaw, Kao, and Chiu 2008), biometric (Tseng et al. 2014), bioinformatics (Leung et al. 2015) applications . Because of wide range system applications, bio-sense might be an indispensable information system our future life.

This special issue collected excellent papers of unpublished research of bio-sense information systems; it includes six high quality works to this special issue. The first and second papers are ‘A sonography image processing system for tumour segmentation’ and ‘Prediction of chronic kidney disease stages by renal ultrasound imaging’. They employed machine learning approaches to biomedical image processing. The first paper design a method to detect the different stages of chronic kidney disease with decisive area-proportional, textural features and support-vector-machine techniques. It can be an auxiliary tool to discover potential patients at the early stages and provide suitable clinical treatments for better therapies. The second paper developed an image segmentation method with Edge Attraction Force on Chan and Vese model to achieve a better extraction of weak edges in noisy speckle images, which is a very important prepossessing for many computer-aided diagnoses.

The third and fourth articles are ‘A Novel Compact Cat Swarm Optimization Based on Differential Method’ and ‘Differential evolution utilizing a handful top superior individuals with a bionic bi-population structure for the enhancement of optimization performance’, respectively. These two works are bio-inspired algorithms for optimisation problems. In compact cat swarm optimisation work, it is designed to solve application domains plagued with limited memory and less-computation power. The fourth article proposes a new DE variant incorporating a new mutation strategy and a bionic bi-population structure to enhance the overall performance of the canonical differential evolution algorithm.

In ‘Use of neurometrics to choose optimal advertisement method for omnichannel business’, it presents an empirical method to record ‘neurometric’ information of respondents and train a computer for predicting expected ‘neurometric’ response for an advertisement channel. The interesting term ‘neurometric’ makes use of eye-tracking, biometric information, implicit response testing, and facial action coding to understand and record sentiment-based human feedback.

The sixth bio-sense related work is ‘Applying time-constraint access control of personal health record in cloud computing’, which is related bioinformatics of healthcare application. This work aims to construct an authority management mechanism that ensures that an authorised medical personnel can obtain a decryption key only in the legal time interval. As an increase of public self-consciousness, this work can be used to promote the use of bio-informatics systems.

Disclosure statement

No potential conflict of interest was reported by the author.