editorial bioinformatics/medical informatics in traditional medicine

EditorialBioinformatics/Medical Informatics in Traditional Medicine andIntegrative Medicine

Zhaohui Liang,1 Xiangji Huang,2,3 Byeongsang Oh,4 and Josiah Poon5

1York University, Toronto, ON, Canada2School of Computer Science, Central China Normal University, Wuhan, China3School of Information Technology, York University, Toronto, ON, Canada4Sydney Medical School, The University of Sydney, Sydney, Australia5School of Information Technologies, Faculty of Engineering and Information Technologies,TheUniversity of Sydney, Sydney, Australia

Correspondence should be addressed to Zhaohui Liang; [email protected]

Received 27 September 2015; Accepted 13 October 2015

Copyright © 2015 Zhaohui Liang et al. This is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Traditional Chinese Medicine (TCM) and integrativemedicine are key components of the cultural heritage fromEastern Asia with thousands-of-years history in research andhealthcare delivery. Traditional orientalmedicine contributessignificantly to the prosperity of Chinese and Eastern Asianculture. After the introduction of western biomedicine toAsia, traditional medicine still plays an important role in thehealthcare system of many Asian countries and integratedwith the mainstream medical treatments as a new track ofhealthcare named as integrative medicine. With the currenttrend of globalization, traditional medicine and integrativemedicine are receiving gradual acceptance in the Westernworld. As a result, studies on traditional medicine attractmore and more attention from researchers with variousknowledge backgrounds and technologies.

Medical informatics is a new interdisciplinary branchin medical science when computer science and informationtechnology are combined with research of health science.The application of medical informatics that has extended tothe studies of traditional medicine and other therapies ofcomplementary and alternative medicine (CAM).

The special issue supported by this journal provides aforum for traditional and integrative medical researchers andpractitioners to share and exchange their new ideas on usingcomputer science and information technology to exploreand solve problems in healthcare. It is proposed with theFifth InternationalWorkshop on Information Technology for

Chinese Medicine (ITCM 2014) in Guangzhou, China, on 12to 14 December 2014. The workshop is in conjunction withthe 2014 IEEE International Conference on Bioinformaticsand Biomedicine (BIBM’14), which was held in Belfast, UK,on 2 to 5 November 2014. Professor Xusheng Liu, ProfessorHonglai Zhang, and Professor Guozheng Li cochaired theworkshop. The conference invited top experts from the US,UK, Australia, and Hong Kong to present their inspiringresearch outcomes and prospect the future of traditionaland integrative medicine. However, numerous scientists andresearchers were unable to introduce their excellent idea dueto time limit of the workshop.

The ITCM 2014 received about 100 submissions. Allpapers were anonymously reviewed by members of the IEEEconference organization committee. The accepted paperswere published in the Proceedings of the 2014 IEEE Inter-national Conference on Bioinformatics and BiomedicineWorkshops (IEEE-BIBMW) (ISBN 978-1-4799-1309-1). Just afew excellent paperswere later invited to submit the extensionversion to the special issue alongside external submissions forconsideration of publishing.This special issue has received 37submissions. All papers have gone through rigorous view, andonly 10 of them (27%) are finally accepted for publication.

This special issue reflects the up-to-date progress inapplications of information technology to traditional andintegrative medicine. The papers are categorized to repre-sent the four aspects of medical informatics research of

Hindawi Publishing Corporatione Scientific World JournalVolume 2015, Article ID 460490, 2 pageshttp://dx.doi.org/10.1155/2015/460490

2 The Scientific World Journal

the discipline. In the paper entitled “Standardization ofSyndrome Differentiation Defined by Traditional ChineseMedicine in Operative Breast Cancer: A Modified DelphiStudy,” Q. Guo and Q. Chen present their research onTCM syndromes. Five papers are selected to demonstratethe research progress in disease diagnosis and treatment. G.-X. Shi et al. report a clinical study on vascular dementia.Z. Chen presents a new mathematics method to explorethe classical theory of five elements in TCM in his work“Researches on Mathematical Relationship of Five Elementsof Containing Notes and Fibonacci Sequence Modulo 5.”In “Syndrome Differentiation Analysis on MARS500 Dataof Traditional Chinese Medicine,” Y.-Z. Li et al. succeed touse MARS500 to process the data of traditional medicine.The paper entitled “Detecting Disease in Radiographs withIntuitive Confidence” by S. Jaeger introduces the new idea touse informatics method to detect disease. Three papers areabout information processing of traditional medicine. Thepaper entitled “Patterns Exploration on Patterns of EmpiricalHerbal Formula of Chinese Medicine by Association Rules”by L. Huang et al. used association rules to retrieve patternsfrom classical traditional medical formula. B. Zhang et al.proposed a bioinformatics approach to explore the latentpatterns from conventional formula Shuang-Huang-Lian intheir work “Using Bioinformatics Approach to Explore thePharmacological Mechanisms of Multiple Ingredients inShuang-Huang-Lian.” The paper entitled “Pulse-DiagnosisSignals Analysis of Fatty Liver Disease and Cirrhosis PatientsbyUsingMachine Learning” byN.Wang et al. introduces newdata mining method to process diagnostic data of liver dis-ease. Finally, the paper entitled “AnEnsemble LearningBasedFramework for Traditional Chinese Medicine Data Analysiswith ICD-10 Labels” by G. Zhang et al. and the paper entitled“ISMAC: An Intelligent System for Customized Clinical CaseManagement and Analysis” introduce the applications ofmachine learning to electronic data analysis of traditionalmedicine.

Acknowledgments

The editors would like to extend their gratitude to the authorsfor their contribution to this special issue, especially to thecorresponding authors, theChair of the steering committee ofBIBM, Professor Xiaohua Tony Hu, and the Program Chairsof ITCM: Professor Guozheng Li, Professor Xusheng Liu, andProfessor Honglai Zhang. The research and editorial work issupported by Natural Science Foundation of China (Grantsnos. 81573827, 81373883, and 81274003) and by the NaturalSciences and Engineering Research Council (NSERC) ofCanada.

Zhaohui LiangXiangji HuangByeongsang Oh

Josiah Poon

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