Health Informatics Data Analysis Methods and Examples
This book provides a comprehensive overview of different biomedical data types, including both clinical and genomic data. Thorough explanations enable readers to explore key topics ranging from electrocardiograms to Big Data health mining and EEG analysis
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Dong Xu May D. Wang Fengfeng Zhou Yunpeng Cai Editors
Health Informatics Data Analysis Methods and Examples
Health Information Science Series editor Yanchun Zhang, Victoria University, Melbourne, Victoria, Australia Editorial Board Riccardo Bellazzi, University of Pavia, Italy Leonard Goldschmidt, Stanford University Medical School, USA Frank Hsu, Fordham University, USA Guangyan Huang, Victoria University, Australia Frank Klawonn, Helmholtz Centre for Infection Research, Germany Jiming Liu, Hong Kong Baptist University, Hong Kong Zhijun Liu, Hebei University of Engineering, China Gang Luo, University of Utah, USA Jianhua Ma, Hosei University, Japan Vincent Tseng, National Cheng Kung University, Taiwan Dana Zhang, Google, USA Fengfeng Zhou, College of Computer Science and Technology, Jilin University, Changchun, China
With the development of database systems and networking technologies, Hospital Information Management Systems (HIMS) and web-based clinical or medical systems (such as the Medical Director, a generic GP clinical system) are widely used in health and clinical practices. Healthcare and medical service are more data-intensive and evidence-based since electronic health records are now used to track individuals’ and communities’ health information. These highlights substantially motivate and advance the emergence and the progress of health informatics research and practice. Health Informatics continues to gain interest from both academia and health industries. The significant initiatives of using information, knowledge and communication technologies in health industries ensures patient safety, improve population health and facilitate the delivery of government healthcare services. Books in the series will reflect technology’s cross-disciplinary research in IT and health/medical science to assist in disease diagnoses, treatment, prediction and monitoring through the modeling, design, development, visualization, integration and management of health related information. These technologies include information systems, web technologies, data mining, image processing, user interaction and interfaces, sensors and wireless networking, and are applicable to a wide range of health-related information such as medical data, biomedical data, bioinformatics data, and public health data.
More information about this series at http://www.springer.com/series/11944
Dong Xu May D. Wang Fengfeng Zhou Yunpeng Cai •
•
Editors
Health Informatics Data Analysis Methods and Examples
123
Editors Dong Xu Digital Biology Laboratory, Computer Science Department University of Missouri-Columbia Columbia, MO USA May D. Wang Georgia Institute of Technology and Emory University Atlanta, GA USA
ISSN 2366-0988 Health Information Science ISBN 978-3-319-44979-1 DOI 10.1007/978-3-319-44981-4
Fengfeng Zhou College of Computer Science and Technology Jilin University Changchun China Yunpeng Cai Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen, Guangdong China
ISSN 2366-0996
(electronic)
ISBN 978-3-319
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