Technical Program 研 讨 会 程 序 手 册 The International Workshop on Information Technology for Chinese Medicine (ITCM2011) 2011 国 际 中 医 信 息 学 研 讨 会 In Conjunction with IEEE-BIBM2011 ( 与 IEEE-BIBM2011 共 同 举 行 ) November 12, 2011, Atlanta, GA, USA Tongji University Guangdong Provincial Hospital of TCM
Catalog Message from the Program Chairs... 1 ITCM 2011 Organization... 2 The Compendiary Atlanta Map... 4 会 程 安 排 表... 5 Schedule Overview... 6 Invited Talk... 7 Arrangement of Oral Presentations... 12
Message from the Program Chairs Welcome to The 2011 International Workshop on Information Technology for Chinese Medicine being held in Atlanta, USA on November 12, 2011. Traditional Chinese Medicine has met a great opportunity with the development of China, where information technology becomes a critical technology to produce great achievements in designing information systems to mine the ancient and present literatures and clinical data, as well as to make objectivity of traditional diagnostics and formula. The ITCM2011 is aimed at providing a common platform to bridge these very important interdisciplinary areas into an interactive forum, and bringing together top researchers, practitioners and students from around the world in order to promote scientific understanding and findings in information technologies and Chinese Medicine. It is sponsored by BIBM2011, Tongji University, and Guangdong Provincial Hospital of Traditional Chinese Medicine, China. The program committee consists of 26 committee members around the world. All submitted papers have been peer-reviewed by the program committee members or invited external reviewers. A total of 39 papers have been selected, and registered authors are from 3 countries including Australia, China, and USA. The conference features one distinguished keynote speakers. Many individuals have contributed to the success of this conference. Many thanks go to all the authors, invited speakers and conference organizers with special thanks to The BIBM steering committee Chair Tony Hu. Special thanks go to the organizing chair Prof. AiHua Ou, Dr. Mingyu You, and local organizing committee consisting of Mrs. Jiaming Liu and Sheng Sun for their assistance. We wish everybody an enjoyable and fruitful stay in Atlanta. Program Chairs ChuanJian Lu, Joe Zhang, GuoZheng Li 1
ITCM 2011 Organization Program Committee Chair: ChuanJian Lu, Guangdong Hospital of Traditional Chinese Medicine, China Joe Zhang, University of Southern Mississippi, USA Guo-Zheng Li, Tongji University, China Organizing Chair: Aihua Ou, Guangdong Hospital of Traditional Chinese Medicine, China Mingyu You, Tongji University, China Program Committee Members: Dan Xi, National Cancer Institute, USA Guo- Zheng Li, Tongji University, China Josiah Poon, The University of Sydney Lei Zhang, The Hong Kong Polytechnic University Xiaoshu Zhu, University of Western Sydney Li- Jun Bai, Institute of Automation, Chinese Academy of Sciences Zhi- Wei Cao, Tongji University Xue- Qiang Zeng, Nanchang University Jian- Xin Chen, Institute of Automation, Chinese Academy of Sciences Zhi- Jin Guan, Nanjing University of Aeronautics and Astronautics Fu- Feng Li, Shanghai University of Traditional Chinese Medicine Kun Li, China Academy of Traditional Chinese Medical Sciences Xiao- Qiang Li, Shanghai University Guo- Ping Liu, Shanghai University of Traditional Chinese Medicine Jian- Feng Lu, Nanjing University of Science and Technology Kun- Bao Tsai, Chongqing University Jian- Jun Yan, East China University of Science and Technology Hai- Xia Yan, Shanghai University of Traditional Chinese Medicine Lian- Wen Zhang, The Hong Kong University of Science & Technology Chang- Le Zhou, Xiamen University Xue- Zhong Zhou, Beijing Jiaotong University Wen- Cong Lu, Shanghai University Yanqing Zhang, Georgia State University Kai- Yun Mi, GE Xun- Sheng Zhu, Suzhou University Wen- Bin Fu, GuangDong Hospital Of Traditional Chinese Medicine Xin- Feng Guo, GuangDong Hospital Of Traditional Chinese Medicine Simon Poon, THE UNIVERSITY OF SYDNEY Yan Li, GuangDong Hospital Of Traditional Chinese Medicine Ying- Rong Lao, GuangDong Hospital Of Traditional Chinese Medicine 2
Ning Tian, GuangDong Hospital Of Traditional Chinese Medicine Da- Ji Xu, GuangDong Hospital Of Traditional Chinese Medicine Jing- Qing Hu, Guang'anmen Hospital,China Academy of Chinese Medical Sciences Ze- Huai Wen, GuangDong Hospital Of Traditional Chinese Medicine Xiao- Bo Yang, GuangDong Hospital Of Traditional Chinese Medicine Ai- Ping Lu, China Academy of Chinese Medical Sciences Shi- Jun Zhang, GuangDong Hospital Of Traditional Chinese Medicine Zhao- Hui Liang, GuangDong Hospital Of Traditional Chinese Medicine Da- Rong Wu, GuangDong Hospital Of Traditional Chinese Medicine 3
The Compendiary Atlanta Map 4
会 程 安 排 表 时 间 日 期 11 月 11 日 11 月 12 日 上 午 下 午 晚 上 注 册 (15:30 pm -20:30 pm) 地 点 :Marriott Atlanta Marquis 大 厅 注 册 口 头 报 告 无 08:30-9:00 am 主 持 人 : 李 艳 地 点 : 一 楼 大 厅 地 点 :Rooms 4-7 开 幕 式 SE225 (1:40 pm 2:10 pm) (9:00 am 9:20 am) SE215 (2:10 pm 2:40 pm) 地 点 :Rooms 4-7 SE217(2:40 pm 3:10 pm) 主 持 :Joe Zhang SE202(3:10 pm 3:40 pm) 欢 迎 辞 :Tony Hu 茶 歇 邀 请 报 告 (3:40 pm 4:20 pm) 主 持 人 :Joe Zhang 报 告 人 : 周 雪 忠 (9:20 am 10:00am) 茶 歇 & 集 体 照 (10:00 am 10:20 am) 11 月 13 日 主 持 人 : 欧 爱 华 报 告 人 : 梁 兆 晖 (10:20 am 11:00 am) 报 告 人 : 张 文 然 (11:00 am 11:40 am) 报 告 人 : 梁 志 伟 (11:40 am 12:20 am) 午 餐 地 点 : 自 由 (12:20 am 1:40 pm) BIBM 大 会 & 离 开 5
Schedule Overview Time Date Nov. 11 Nov. 12 Morning Afternoon Evening Registration (3:30 pm -8:30 pm) Venue: Marriott Atlanta Marquis Registration Oral Presentation: (08:30am-09:00am) Chair: Zhaohui Liang Venue :the ground floor of Venue:Rooms 4-7 the conference venue SE225 (1:40 pm 2:10 pm) SE215 (2:10 pm 2:40 pm) Opening Ceremony SE217(2:40 pm 3:10 pm) (9:00 am 9:20 am) SE202(3:10 pm 3:40 pm) Venue: Rooms 4-7 Coffee Break Chair: Joe Zhang (3:40 pm 4:20 pm) Welcome Message: Tony Hu Invited Talk Chair: Joe Zhang Speaker: Xuezhong Zhou (9:20 am 10:00 am) Coffee Break &Take Photo (10:00 am 10:20 am) Chair: AiHua Ou Speaker: Zhaohui Liang (10:20 am 11:00 am) Speaker: Wen-Ran Zhang (11:00 am 11:40 am) Speaker: Zhiwei Liang (11:40 am 12:20 am) Nov. 13 Lunch (at your own) (12:30 am 1:40 pm) BIBM Conference & Departure 6
Invited Talk Title: Data processing and analysis in real-world traditional Chinese medicine clinical data: challenges and approaches Abstract: Traditional Chinese medicine (TCM) is a clinical-based discipline in which real-world clinical practice plays a significant role for both the development of clinical therapy and theoretical research. The large-scale clinical data generated during the daily clinical operations of TCM provide a highly valuable knowledge source for clinical decision making. Secondary analysis of these data would be a vital task for TCM clinical studies before the randomised controlled trials are conducted. In this article, we discuss the challenges and issues, such as structured data curation, data preprocessing and quality, large-scale data management and complex data analysis requirements, in the data processing and analysis of real-world TCM clinical data. Furthermore, we also discuss related state-of-the-art research and solutions in China. We have shown that the clinical data warehouse based on the collection of structured electronic medical record data and clinical terminology would be a promising approachfor generating clinical hypotheses and helping the discovery of clinical knowledge from large-scale real-worldtcm clinical data. Xuezhong Zhou, Xuezhong Zhou is currently an associate professor in College of Computer Science and Information Technology, Beijing Jiaotong University. He received a PhD degree in Computer Science from Zhejiang University, China and carried out postdoctoral research at China Academy of Chinese Medical Sciences. His research interests cover machine learning and data mining with focus on its application to biomedical informatics. Particularly, he takes main efforts to develop novel computational approaches for Traditional Chinese Medicine (TCM) warehousing, knowledge discovery, modeling and evaluation, and its integration into modern biomedical information. 7
Title: Machine learning algorithms and the application to clinical assessment of acupuncture Abstract: Machine learning is to deal with the design and development of algorithms to allow computers to evolve behaviors based on empirical data. Its application to clinical assessment is to develop algorithms that allow the system to learn via inductive inference based on the available data acquired from relatively small sample size and attempt to generalize it to rules and make predictions on missing attributes or future data. The algorithms of machine learning is able to recognized the pattern complexity of clinical data of Chinese medicine, such as TCM syndromes, patients attitude and their subjective feelings towards the treatment etc; and then it can distinguish between exemplars based on their different patterns, and to make intelligent predictions on their sub-type, such as the difference of TCM syndrome types and the difference between Chinese medicine diagnosis and its western medicine counterparts. In our studies, the application of machine learning to automatically classification began firstly as an attempt to content mining of Chinese medicine literature, in which an support vector machine algorithm based on prior knowledge was developed to classify a data set containing more than 300,000 records of TCM syndrome related literature. Currently, we attempt to apply the algorithms including kernel-as-similarity feature representation, non-dominated sort (NDS), kernel canonical correlation analysis (KCCA) and local learning, to analyze the clinical data of a multi-center RCT study on acupuncture for neck pain caused by cervical spondylosis. The above algorithms were respectively applied to classify and analyze Chinese medical syndromes, diagnostic sub-types of TCM disease and the similarity and discrepancy of different clinical effect indexes. The outcomes indicate that machine learning is an effective approach to accurately classify syndromes and other sub-type diagnosis under the theoretical framework of Chinese medicine when the algorithm models are properly trained by empirical data. Since conducting high quality clinical trials often means high cost on the one hand, and the current interim analysis strategy is challenged for its failure to protect patients and leading to biased results on the other hand, to introduce a robust analytic method to evaluate the clinical data and correctly predict its efficacy as an alternative assess is meaningful for the future of clinical studies of Chinese medicine. The intuition behind our work is to construct a new model for interim analysis of clinical trial based on data mining methods. By using the data of pilot studies as outstanding samples for model training instead of the whole data set, the machine learning analytic method can reduce the sample size of training set while keeping model of the same or better effect as that of the whole data set in transductive learning setting. The exciting finding in our study is that in the outcome prediction model, if a record sample similarity based method is applied, not only records of good effect but also negative ones helps to improve the accuracy of the target model. And we believe the machine learning approach is an ideal option for data analysis of clinical studies of Chinese medicine, and it is feasible to detect the underly rules of 8
the individualized clinical practice and effect of Chinese medicine. Zhaohui Liang, I received my Bachelor of Medicine in Chinese Medical Rehabilitation in 2003. From July 2003 to February 2004, I worked in the central laboratory of Guangdong Provincial Hospital of Chinese Medicine as research assistant. My work responsibility included the monitoring of drug plasma concentration of patients and pharmacokinetics studies. From March 2004 to October 2005, I worked in the department of research administration with the regular responsibility to manage the on-going studies projects and documentation. I passed the National Examination for Medical Practitioners in 2004 and registered as certificated medical practitioner since October 2005. Then from November 2005 to December 2009, I worked as medical doctor specialized in Chinese medicine and acupuncture in Guangdong Provincial Hospital of Chinese Medicine, and I was promoted as physician-in-charge specialized in Chinese medicine and acupuncture since January 2010. During my work, I finished my Master degree in medicine in Guangzhou University of Chinese Medicine in 2008 and my Master of Public Health (MPH) in Sun Yat-sen University in 2009. I pursued my doctorate study since September 2010 in Guangzhou University of Chinese Medicine. My research interests include: 1) study methodology of Chinese medicine, integrative medicine and complementary and alternative medicine (CAM); 2) clinical trials on acupuncture and Chinese medicine for pain and neurosis and depressive disorders; 3) metabolomics and its application on anti-aging and anti-stress; 4) the application of bioinformatics in research of Chinese medicine and integrative medicine. I have been trained as an acupuncture specialist for more than 12 years, and I am familiar with the relevant knowledge and principles of Chinese medicine. With the MPH study experience in Sun Yat-sen University, I acquired the knowledge and skills in epidemiology, biostatistics and research methodology. In particular, my research skills include the use of statistical software (e.g. SPSS, AMOS, and EpiData etc.) for data analysis of medical studies, clinical skills in acupuncture, literature study with the use of biomedical database (e.g. PubMed, EMBASE, Cochrane Database etc.) and EndNote, and skill in evidence-based medicine studies. In addition, I have been the secretary of Ethics Committee of Guangdong Provincial Hospital of Chinese Medicine since August 2006, and I am familiar with the regulations of ethics review of ICH-GCP. In 2010, we acquired the WHO-SIDCER Recognition for Ethics Review Operation and Ethics Committees, and I became a member of SIDCER-FERCAP, which is an influential NGO of bioethics in Asia. In academic, I have published 16 papers as the first author or corresponding author, and another 14 papers as co-author. Particularly since 2009, my work has been published in high quality peer-reviewed journals, in which five of them were published in SCI-indexed journals. 9
Title: The YinYang Bipolar relativity and Bio-Quantum Computing Abstract: YinYang bipolar relativity and its applications in bio-quantum computing are introduced in this talk focused on the scientific foundation of TCM. Based on YinYang bipolar dynamic logic and bipolar quantum linear algebra, a bipolar quantum gravity model of atom is proposed for the unification of matter and antimatter, particle and wave as well as relativity and quantum mechanics. The modeling and simulation of bipolar quantum cellular structures are analyzed and discussed aimed at equilibrium-based molecular interaction. These range from YinYang-5-Elements to YinYang-N-Elements modeling and simulation. Some simulation results are analyzed. It makes the ubiquitous effects of quantum entanglement comprehensible in simple logical terms and forms. It brought up for the first time the possibility of a scientific reincarnation and unification of East and West philosophical traditions. Wen-Ran Zhang, Ph.D. in electrical and computer engineering. He is currently professor and interim chair of computer science at Georgia Southern University. Professor Zhang is the author of more than 80 refereed publications. He is the founder of YinYang bipolar sets and logic, bipolar quantum entanglement, bipolar quantum linear algebra, and bipolar quantum cellular automata. He is the author of the recent monograph titled: YinYang Bipolar Relativity: A Unifying Theory of Nature, Agents and Causality with Applications in Quantum Computing, Cognitive Informatics and Life Sciences 10
Title: The model of high-order multidimensional tree with tristate applied to the digitalization of Yin-Yang theory of Traditional Chinese Medicine Abstract: [Objective] To approach the digital reciprocal expression with undamaged information about the topology of the high-order multidimensional tree with sequenced nodes (HMTSN) and to build method for calculating the characteristic discrepancy of state-space between HMTSN, this paper applies mapping and matrix theory to seek for the potential applicability in biomedical field, especially in Traditional Chinese Medicine (TCM). [Methods] 1. Applying n-dimensional spatial vector representation, as well as set and mapping theory, this research mappings HMTSN to a characterized square matrix (CSM) based on a customer-set protocol; 2. Calculating the differences in value between the elements from two different square matrices being mapped from corresponding tree spatial status, the result obtains the difference between two multidimensional structures with multi-state.[results] 1. With a special case with {-1,0, +1} in effective nodes, HMTSN can be used to describe the characteristics of multidimensional structure in Yin-Yang differentiation of TCM(DIFF) with tristate; 2. The customer-set protocol is satisfied to reciprocally and fully express the characterized of HMTSN with CSM through mapping from HMTSN model to a matrix; 3. The square root of the matrix trace (SRMT) calculated from two CSM, which is the matrix product made by the difference between square matrices (DSM) multiplied by the transpose of DSM, may reflect the structural difference in value between HMTSN. HMTSN with tristate and SRMT may express the Yin-Yang DIFF and have potential benefit for its transmission study. [Conclusions] The matrixing for the model of HMTSN and its algorithm, as a special case of tristate with Yin, Balance and Yang, being as a method of the DIFF and a potential algorithm for DIFF transmission in TCM with the core of Yin and Yang, may offer a creative metrizable method for TCM theory. Zhiwei Liang 11
Arrangement of Oral Presentations Chair: Yan Li 1:40 pm 3:40 pm, November 12 2011, Room 4-7 SE225 SE215 SE217 SE202 TCM Syndromes Diagnostic Model of hypertension:study based on Tree Augmented Naive Bayes Wen-wei Ouyang, Xiao-zhong Lin, Yi Ren, Yi Luo, Yun-tao Liu, Jia-min Yuan, Ai-hua Ou, and Guo-zheng Li Application of Data Mining Technology in Excavating Prevention and Treatment Experience of Infectious Diseases From Famous Old Herbalist Doctors Yi Luo, Jian Yin, Ji-Qiang Li, Dan-Wen Zheng, Zhan-Peng Tan, Hong Zhou, Qing-Ping Deng, Yun-Tao Liu, and Ai-hua Ou Lifted Wavelet Transforms with Application to Human Pulse Identification Kunbao CAI, Long WAN, and Decheng LUO A Randomized, controlled Study of Efficacy and Safety on Mild to moderate Insomnia intervened by Chinese Medicine in the Integrated Program Yan Li, Biyun Xu, Shuhui Chen, Peng Liu, Aihua Ou, Yan Xu, Zehuai Wen, Biyang Ou, Ruiyu Xu, zhaozhang Wei, and Liang Zeng 12