Beschreibung:
Hsinchun Chen is McClelland Professor of Management Information Systems (MIS) at the Eller College of the University of Arizona and Andersen Consulting Professor of the Year (1999). He is the author of 15 books and more than 200 articles covering knowledge management, digital library, homeland security, Web computing, and biomedical informatics in leading information technology publications. He serves on ten editorial boards, including: Journal of the American Society for Information Science and Technology, ACM Transactions on Information Systems, IEEE Transactions on Systems, Man, and Cybernetics, IEEE Transactions on Intelligent Transportation Systems, International Journal of Digital Library, and Decision Support Systems. He has served as a Scientific Advisor/Counselor of the National Library of Medicine (USA), Academia Sinica (Taiwan), and National Library of China (China). Dr. Chen founded The University of Arizona Artificial Intelligence Lab in 1990. The group is distinguished for its applied and high-impact AI research. Since 1990, Dr. Chen has received more than $20M in research funding from various government agencies and major corporations. He has been a PI of the NSF Digital Library Initiative Program and the NIH NLM s Biomedical Informatics Program. His group has developed advanced medical digital library and data and text mining techniques for gene pathway and disease informatics analysis and visualization since 1995. Dr. Chen s nanotechnology patent analysis works, funded by NSF, have been published in the Journal of Nanoparticle Research. His research findings were used in the President s Council of Advisors in Science and Technology s report on "The National Nanotechnology Initiative at Five Years: Assessment and Recommendations of the National Nanotechnology Advisory Panel." Dr. Chen s work also has been recognized by major US corporations and been awarded numerous industry awards for his contribution to IT education and research, including: ATT Foundation Award in Science and Engineering and SAP Award in Research/Applications. Dr. Chen has been heavily involved in fostering digital library, medical informatics, knowledge management, and intelligence informatics research and education in the US and internationally. He has been a PI for more than 20 NSF and NIH research grants since 1990. Dr. Chen is conference chair of ACM/IEEE Joint Conference on Digital Libraries (JCDL) 2004 and has served as the conference general chair or international program committee chair for the past six International Conferences of Asian Digital Libraries (ICADL), 1998-2005. He has been instrumental in fostering the ICADL activities in Asia. Dr. Chen is the founder and also conference co-chair of the IEEE International Conference on Intelligence and Security Informatics (ISI), 2003-2006. The ISI conference has become the premiere meeting for international, national, and homeland security IT research. Dr. Chen is an IEEE fellow.
Computer-based infectious disease surveillance systems represent a major step forward in disease surveillance. This book analyzes and evaluates the outbreak modeling and detection capabilities of existing surveillance systems under a unified framework.
Examines the state of the art in disease surveillance systems
SYNDROMIC SURVEILLANCE SYSTEMS.- Infectious Disease Informatics: An Introduction and An Analysis Framework.- Public Health Syndromic Surveillance Systems.- Syndromic Surveillance Data Sources and Collection Strategies.- Data Analysis and Outbreak Detection.- Data Visualization, Information Dissemination, and Alerting.- System Assessment and Evaluation.- SYNDROMIC SURVEILLANCE SYSTEM CASE STUDIES.- BioSense.- RODS.- BioPortal.- ESSENCE.- New York City Syndromic Surveillance Systems.- EARS.- Argus.- HealthMap.- Challenges and Future Directions.
Computer-based infectious disease surveillance systems are capable of real-time or near real-time detection of serious illnesses and potential bioterrorism agent exposures and represent a major step forward in disease surveillance. Infectious Disease Informatics: Syndromic Surveillance for Public Health and Bio-Defense is an in-depth monograph that analyzes and evaluates the outbreak modeling and detection capabilities of existing surveillance systems under a unified framework, and presents the first book-length coverage of the subject from an informatics-driven perspective.
Individual chapters consider the state of the art, including the facilitation of data collection, sharing and transmission; a focus on various outbreak detection methods; data visualization and information dissemination issues; and system assessment and other policy issues. Eight chapters then report on several real-world case studies, summarizing and comparing eight syndromic surveillance systems, including those that have been adopted by many public health agencies (e.g., RODS and BioSense). The book concludes with a discussion of critical issues and challenges, with a look to future directions.
This book is an excellent source of current information for researchers in public health and IT. Government public health officials and private-sector practitioners in both public health and IT will find the most up-to-date information available, and students from a variety of disciplines, including public health, biostatistics, information systems, computer science, and public administration and policy will get a comprehensive look at the concepts, techniques, and practices of syndromic surveillance.
