The Detection of Opioid Misuse and Heroin Use From Paramedic Response Documentation: Machine Learning for Improved Surveillance

Timely, precise, and localized surveillance of nonfatal events is needed to improve response and prevention of opioid-related problems in an evolving opioid crisis in the United States. Records of naloxone administration found in prehospital emergency medical services (EMS) data have helped estimate...

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Vydáno v:	Journal of medical Internet research Ročník 22; číslo 1; s. e15645
Hlavní autoři:	Prieto, José Tomás, Scott, Kenneth, McEwen, Dean, Podewils, Laura J, Al-Tayyib, Alia, Robinson, James, Edwards, David, Foldy, Seth, Shlay, Judith C, Davidson, Arthur J
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Canada Gunther Eysenbach MD MPH, Associate Professor 03.01.2020 JMIR Publications
Témata:	Agreements Algorithms Artificial intelligence Classification Documentation Drug abuse Drug overdose Emergency services First responders Health services Heroin Information Keywords Machine learning Machinery Management Multimedia Naloxone Narcotics Narratives Natural language processing Opioids Original Paper Overdoses Paramedics Prevention Public health Support vector machines Surveillance Trends Unconsciousness United States > US Colorado emergency medical services opioid crisis heroin natural language processing substance-related disorders naloxone artificial intelligence
ISSN:	1438-8871, 1439-4456, 1438-8871
On-line přístup:	Získat plný text
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