JCSE, vol. 11, no. 4, pp.109-110, 2017

DOI:

Preface for the Special Issue on Computational Intelligence Technologies Meets Medical informatics

Chi-Chang Chang, Chi-Jie Lu, and Chalong Cheewarkriangkrai
School of Medical Informatics, Chung Shan Medical University, Taiwan Department of Industrial Management, Chien Hsin University of Science and Technology, Taiwan Division of Gynecologic Oncology, Department of Obstetrics and Gynecology Faculty of Medicine, Chiang Mai University, Thailand

Abstract: The healthcare of the challenges is facing ongoing dramatic paradigm shifts thanks to the computational intelligence research and the advancement of information technologies [1,2,3]. Medical informatics is an interdisciplinary scientific field [4,5]. It deals with developing and applying advanced methods in order to better understand and to improve healthcare, via the diagnosis, treatment, and prevention of disease, illness, injury, and other physical and mental impairments in human beings [6,7,8]. This special issue aims at providing a comprehensive overview of state-of-the-art research and applications of computational intelligence. In this special issue, we have received 20 high-quality submissions from the International Conference on Medical and Health Informatics 2017 (ICMHI 2017) and the public, reflecting the intersection of computational intelligence technologies and medical/health informatics. High quality articles of theoretical developments and empirical studies with scientific novelty and insights were reviewed by the scholars in medicine fields. After two rounds of reviews involving 40 reviewers, we were able to select 4 manuscripts to form the special issue that we now present. The paper ??弛춅ntifying Post-Translational Modification Crosstalks for Breast Cancer??by Tung et al. focuses on the interactions between Post-translational modifications (PTMs) of breast cancer-related proteins that were comprehensively investigated using sequence and domain information and the application of bioinformatics methods. Based on the interactive effects of PTMs, results reveal that the present model allows biologists to further explore the regulatory pathways of biological functions and related diseases. The paper ??夷럂ture Selection Via Embedded Learning Based on Tangent Space Alignment for Microarray Data??by Ye and Sakurai proposes a novel unsupervised feature selection method for gene selection in microarray data analysis. The proposed method incorporates embedded learning and sparse regression into a framework for selecting the informative genes which better capture the interesting natural classes of samples. Experimental results indicate that the proposed method outperforms other state-of-the-art unsupervised feature selection methods. The paper ??夷럂ture Selection based on Bi-objective Differential Evolution??by Das et al. deals simultaneously with optimizing two feature selection criteria, namely, set approximation accuracy of rough set theory and relational algebra based derived score, in order to select the most relevant feature subset from an entire feature set. Effectiveness of the proposed algorithm is shown by comparing it with other several state of the art feature selection methods by means of different statistical accuracy measures. The paper ???쟢 of Information Technologies to Explore Correlations between Climatic Factors and Spontaneous Intracerebral Hemorrhage in Different Age Groups??by Ting et al. presents the decision tree algorithm and random forest to deal with weather factors that have different influences on the risk of spontaneous intracerebral hemorrhage (sICH) in different age groups. The empirical study clearly shows that the extracted information and knowledge is helpful to enhance decision quality and that the results are easy to understand. While this special issue has successfully addressed some of the critical research needs for medical informatics and computational intelligence for emerging research needs for future research directions, we would like to express our sincere appreciations to the anonymous reviewers for their invaluable contributions to making this special issue a success.

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