Syndromic Surveillance using Twitter Data
نویسندگان
چکیده
منابع مشابه
Syndromic Surveillance using Generic Medical Entities on Twitter
Public health surveillance is challenging due to difficulties accessing medical data in real-time. We present a novel, effective and computationally inexpensive method for syndromic surveillance using Twitter data. The proposed method uses a regression model on a database previously built using named entity recognition to identify mentions of symptoms, disorders and pharmacological substances o...
متن کاملTwitter mining for fine-grained syndromic surveillance
BACKGROUND Digital traces left on the Internet by web users, if properly aggregated and analyzed, can represent a huge information dataset able to inform syndromic surveillance systems in real time with data collected directly from individuals. Since people use everyday language rather than medical jargon (e.g. runny nose vs. respiratory distress), knowledge of patients' terminology is essentia...
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Objective We present an annotation scheme developed to analyze syndromic Twitter data, and the results of its application to a set of respiratory syndrome-related tweets [1]. The scheme was designed to differentiate true positive tweets (where an individual is experiencing respiratory symptoms) from false positive tweets (where an individual is not experiencing respiratory symptoms), and to qua...
متن کاملDetection of Outbreaks in Syndromic Surveillance Data Using Monotonic Regression
Due to nonstationarity and substantial variability in outbreak profiles, early detection of disease outbreaks is challenging. In this paper we propose a method to detect outbreaks in syndromic surveillance data using a generalized likelihood ratio test in which both the null and alternative hypotheses are normally distributed. The data is daily counts of interactions between patients and the Na...
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Introduction NYC Department of Health and Mental Hygiene recently reoriented its oral health care strategy to focus on health promotion and expanded surveillance. One surveillance challenge is the lack of timely OHV data; few dental providers are in our electronic health record project, and statewide utilization data are subject to delays. Prior research has examined OHV using ICD-9-CM from ED ...
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ژورنال
عنوان ژورنال: Emergency Medicine: Open Access
سال: 2015
ISSN: 2165-7548
DOI: 10.4172/2165-7548.1000254