Outcome prediction of methadone poisoning in the United States: implications of machine learning in the National Poison Data System (NPDS)

Author:

Mehrpour Omid12,Saeedi Farhad34,Vohra Varun5,Hoyte Christopher67

Affiliation:

1. Michigan Poison & Drug Information Center, Wayne State University School of Medicine, Detroit, MI, USA

2. Rocky Mountain Poison and Drug Safety, Denver Health and Hospital Authority, Denver, CO, USA

3. Student Research Committee, Birjand University of Medical Sciences, Birjand, Iran

4. Medical Toxicology and Drug Abuse Research Center (MTDRC), Birjand University of Medical Sciences (BUMS), Birjand, Iran

5. Department of Emergency Medicine, Michigan Poison & Drug Information Center, Wayne State University School of Medicine, Detroit, MI, USA

6. University of Colorado Anschutz Medical Campus, Aurora, CO, USA

7. University of Colorado Hospital, Aurora, CO, USA

Publisher

Informa UK Limited

Subject

Chemical Health and Safety,Health, Toxicology and Mutagenesis,Public Health, Environmental and Occupational Health,Pharmacology,Toxicology,General Medicine

Reference14 articles.

1. Nephrotoxicity of methadone: A systematic review;Alinejad S.;SpringerPlus,2016

2. A systematic review of the cardiotoxicity of methadone;Alinejad S.;EXCLI Journal,2015

3. Poisoning in the United States: 2012 Emergency Medicine Report of the National Poison Data System

4. Machine learning based opioid overdose prediction using electronic health records;Dong X.;AMIA. Annual Symposium Proceedings. AMIA Symposium,2019

5. Predicting opioid dependence from electronic health records with machine learning;Ellis R. J.;BioData Mining,2019

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