{"id":262260,"date":"2026-07-13T18:56:14","date_gmt":"2026-07-13T15:56:14","guid":{"rendered":"https:\/\/1kitap1.com\/en\/healthcare-data-analytics-charu-c-agarwal\/"},"modified":"2026-07-13T18:56:14","modified_gmt":"2026-07-13T15:56:14","slug":"healthcare-data-analytics-charu-c-agarwal","status":"publish","type":"post","link":"https:\/\/1kitap1.com\/en\/healthcare-data-analytics-charu-c-agarwal\/","title":{"rendered":"Healthcare Data Analytics – Charu C Agarwal"},"content":{"rendered":"
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Accessed 08-08-2014. David A. Broniatowski, Michael J. Paul, and Mark Dredze. National and local influenza surveillance through Twitter: An analysis of the 2012\u20132013 influenza epidemic. PLoS ONE, 8(12):e83672, 2013. Catherine A. Brownstein, John S. Brownstein, Davis S. Williams, Paul Wicks, and James A. Heywood. The power of social networking in medicine. Nature Biotechnology, 27:888\u2013890, 2009. John S. Brownstein, Clark C. Freifeld, Emily H. Chan, Mikaela Keller, Amy L.<\/p>\n

Sonricker, Sumiko R. Mekaru, and David L. Buckeridge. Information technology and global surveillance of cases of 2009 H1N1 influenza. The New England Journal of Medicine, 362(18): 1731\u20131735, 2010. John S. Brownstein, Clark C. Freifeld, Ben Y. Reis, and Kenneth D. Mandl. Surveillance sans fronti\u00e8res: Internet-based emerging infectious disease intelligence and the HealthMap project. PLoS Medicine, 5(7):e151, 2008. John T. Cacioppo, James H. Fowler, and Nicholas A. Christakis. Alone in the crowd: The structure and spread of loneliness in a large social network. Journal of Personality and Social Psychology, 97(6):977\u2013991, 2009.<\/p>\n

Herman Anthony Carneiro and Eleftherios Mylonakis. Google trends: A web-based tool for real-time surveillance of disease outbreaks. Clinical Infectious Diseases, 49(10):1557\u20131564, 2009. Brant W. Chee, Richard Berlin, and Bruce Schatz. Predicting adverse drug events from personal health messages. In Proceedings of the 2011 AMIA Annual Symposium, pages 217\u2013226, 2011. Cynthia Chew and Gunther Eysenbach. Pandemics in the age of Twitter: Content analysis of tweets during the 2009 H1N1 outbreak. PLoS ONE, 5(11):e14118, 2010. Nicholas A.<\/p>\n

Christakis and James H. Fowler. The spread of obesity in a large social network over 32 years. New England Journal of Medicine, 357:370\u2013379, 2007. Katherine Y. Chuang and Christopher C. Yang. Helping you to help me: Exploring supportive interaction in online health community. Proceedings of the American Society for Information Science and Technology, 47(1): 1\u201310, 2010. [18] [19] [20] [21] [22] [23] [24] [25] Katherine Y.<\/p>\n

Chuang and Christopher C. Yang. Social support in online healthcare social networking. In Proceedings of the 2010 iConference, 2010. Rumi Chunara, Jason R. Andrews, and John S. Brownstein. Social and news media enable estimations of epidemiological patterns early in the 2010 Haitian cholera outbreak. American Journal of Tropical Medicine and Hygiene, 86(1):39\u201345, 2012. Cindy K. Chung, Clinton Jones, and Alexander Liu. Predicting success and failure in weight loss blogs through natural language use. In Proceedings of the 2nd International AAAI Conference on Weblogs and Social Media (ICWSM’08), pages 180\u2013181, 2008.<\/p>\n

Nathan K. Cobb, Amanda L. Graham, and David B. Abrams.<\/p>\n

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This series aims to capture new developments and applications in data mining and knowledge discovery, while summarizing the computational tools and techniques useful in data analysis. This series encourages the integration of mathematical, statistical, and computational methods and techniques through the publication of a broad range of textbooks, reference works, and handbooks. The inclusion of concrete examples and applications is highly encouraged. The scope of the series includes, but is not limited to, titles in the areas of data mining and knowledge discovery methods and applications, modeling, algorithms, theory and foundations, data and knowledge visualization, data mining systems and tools, and privacy and security issues.<\/p>\n

PUBLISHED TITLES ADVANCES IN MACHINE LEARNING AND DATA MINING FOR ASTRONOMY Michael J. Way, Jeffrey D. Scargle, Kamal M. Ali, and Ashok N. Srivastava BIOLOGICAL DATA MINING Jake Y. Chen and Stefano Lonardi COMPUTATIONAL BUSINESS ANALYTICS Subrata Das COMPUTATIONAL INTELLIGENT DATA ANALYSIS FOR SUSTAINABLE DEVELOPMENT Ting Yu, Nitesh V. Chawla, and Simeon Simoff COMPUTATIONAL METHODS OF FEATURE SELECTION Huan Liu and Hiroshi Motoda CONSTRAINED CLUSTERING: ADVANCES IN ALGORITHMS, THEORY, AND APPLICATIONS Sugato Basu, Ian Davidson, and Kiri L.<\/p>\n

Wagstaff CONTRAST DATA MINING: CONCEPTS, ALGORITHMS, AND APPLICATIONS Guozhu Dong and James Bailey DATA CLASSIFICATION: ALGORITHMS AND APPLICATIONS Charu C. Aggarawal DATA CLUSTERING: ALGORITHMS AND APPLICATIONS Charu C. Aggarawal and Chandan K. Reddy DATA CLUSTERING IN C++: AN OBJECT-ORIENTED APPROACH Guojun Gan DATA MINING FOR DESIGN AND MARKETING Yukio Ohsawa and Katsutoshi Yada DATA MINING WITH R: LEARNING WITH CASE STUDIES Lu\u00eds Torgo FOUNDATIONS OF PREDICTIVE ANALYTICS James Wu and Stephen Coggeshall GEOGRAPHIC DATA MINING AND KNOWLEDGE DISCOVERY, SECOND EDITION Harvey J.<\/p>\n

Miller and Jiawei Han HANDBOOK OF EDUCATIONAL DATA MINING Crist\u00f3bal Romero, Sebastian Ventura, Mykola Pechenizkiy, and Ryan S.J.d. Baker HEALTHCARE DATA ANALYTICS Chandan K. Reddy and Charu C. Aggarwal INFORMATION DISCOVERY ON ELECTRONIC HEALTH RECORDS Vagelis Hristidis INTELLIGENT TECHNOLOGIES FOR WEB APPLICATIONS Priti Srinivas Sajja and Rajendra Akerkar INTRODUCTION TO PRIVACY-PRESERVING DATA PUBLISHING: CONCEPTS AND TECHNIQUES Benjamin C. M. Fung, Ke Wang, Ada Wai-Chee Fu, and Philip S. Yu KNOWLEDGE DISCOVERY FOR COUNTERTERRORISM AND LAW ENFORCEMENT David Skillicorn KNOWLEDGE DISCOVERY FROM DATA STREAMS Jo\u00e3o Gama MACHINE LEARNING AND KNOWLEDGE DISCOVERY FOR ENGINEERING SYSTEMS HEALTH MANAGEMENT Ashok N.<\/p>\n<\/blockquote>\n

This is a short excerpt from the opening of “” by Unknown, quoted for review and introduction purposes. All rights belong to the copyright holders.<\/em><\/p>\n

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