TY  - BOOK
AU  - Shaban-Nejad,Arash
AU  - Brownstein,John S.
AU  - Buckeridge,David L.
ED  - SpringerLink (Online service)
TI  - Public Health Intelligence and the Internet
T2  - Lecture Notes in Social Networks,
SN  - 9783319686042
AV  - R858-R859.7 
U1  - 502.85 23
PY  - 2017///
CY  - Cham
PB  - Springer International Publishing, Imprint: Springer
KW  - Health informatics
KW  - Public health
KW  - Mathematics
KW  - Social sciences
KW  - Statistics 
KW  - Health Informatics
KW  - Public Health
KW  - Mathematics in the Humanities and Social Sciences
KW  - Statistics for Life Sciences, Medicine, Health Sciences
N1  - Geographical Mapping and Visual analytics for Health Data -- Social Media Analytics -- Epidemic Intelligence -- Predictive modelling and Decision support -- Biomedical Ontologies, terminologies and standard -- Bayesian Networks and Reasoning under Uncertainty -- Temporal and Spatial Representation and Reasoning -- Case-based Reasoning in Healthcare -- Crowdsourcing, and Collective Intelligence -- Risk assessment, Trust, Ethics, and Privacy -- Sentiment Analysis and Opinion Mining -- Computational Behavioral/Cognitive Modeling -- Applications in Epidemiology and Surveillance (e.g. Bioterrorism, Participatory Surveillance); Available to subscribing member institutions only. Доступно лише організаціям членам підписки
N2  - This book aims to highlight the latest achievements in epidemiological surveillance and internet interventions based on monitoring online communications and interactions on the web. It presents the state of the art and the advances in the field of online disease surveillance and intervention. The edited volume contains extended and revised versions of selected papers presented at the International World Wide Web and Population Health Intelligence (W3PHI) workshop series along with some invited chapters and presents an overview of the issues, challenges, and potentials in the field, along with the new research results. The book provides information for a wide range of scientists, researchers, graduate students, industry professionals, national and international public health agencies, and NGOs interested in the theory and practice of computational models of web-based public health intelligence
UR  - https://doi.org/10.1007/978-3-319-68604-2
ER  -