Predicting opioid dependence from electronic health records with machine learning

Predicting opioid dependence from electronic health records with machine learning

Abstract Background The opioid epidemic in the United States is averaging over 100 deaths per day due to overdose. The effectiveness of opioids as pain treatments, and the drug-seeking behavior of opioid addicts, leads physicians in the United States to issue over 200 million opioid prescriptions ev...

Full description

Bibliographic Details
Main Authors: Randall J. Ellis, Zichen Wang, Nicholas Genes, Avi Ma’ayan
Format: Article
Language:English
Published: BMC 2019-01-01
Series:BioData Mining
Subjects:
Opioid epidemic
Opioid dependence
Electronic health records
Electronic medical records
Machine learning
Artificial intelligence
Online Access:http://link.springer.com/article/10.1186/s13040-019-0193-0

Internet

http://link.springer.com/article/10.1186/s13040-019-0193-0

Similar Items