Machine Learning for Drug Overdose Surveillance
نویسندگان
چکیده
منابع مشابه
Machine Learning for Drug Overdose Surveillance
We describe two recently proposed machine learning approaches for discovering emerging trends in fatal accidental drug overdoses. The Gaussian Process Subset Scan enables early detection of emerging patterns in spatio-temporal data, accounting for both the non-iid nature of the data and the fact that detecting subtle patterns requires integration of information across multiple spatial areas and...
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Introduction Drug overdoses are an increasingly serious problem in the United States and worldwide. The CDC estimates that 47,055 drug overdose deaths occurred in the United States in 2014, 61% of which involved opioids (including heroin, pain relievers such as oxycodone, and synthetics).1 Overdose deaths involving opioids increased 3-fold from 2000 to 2014.1 These statistics motivate public he...
متن کاملDrug overdose surveillance using hospital discharge data.
OBJECTIVES We compared three methods for identifying drug overdose cases in inpatient hospital discharge data on their ability to classify drug overdoses by intent and drug type(s) involved. METHODS We compared three International Classification of Diseases, Ninth Revision, Clinical Modification code-based case definitions using Kentucky hospital discharge data for 2000-2011. The first defini...
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Introduction Although Marin County ranks as the healthiest county in California, it ranks poorly in substance abuse indicators, including drug overdose mortality.1 Death certificates do not always include specific detail on the substances involved in a drug overdose.2 This lack of specificity makes it difficult to identify public health issues related to specific prescription drugs in our commu...
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A common step in drug design is the formation of a quantitative structure-activity relationship (QSAR) to model an exploratory series of compounds. A QSAR generalizes how the structure of a compound relates to its biological activity. There is growing interest in the application of machine learning techniques in QSAR modeling research. However, no single technique can claim to be uniformly supe...
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ژورنال
عنوان ژورنال: Journal of Technology in Human Services
سال: 2018
ISSN: 1522-8835,1522-8991
DOI: 10.1080/15228835.2017.1416511