Data Driven Classification of Opioid Patients Using Machine Learning–An Investigation-Reference-Cited by-同舟云学术

Data Driven Classification of Opioid Patients Using Machine Learning–An Investigation

Published:2023 Issue: Volume:11 Page:396-409
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Amin Saddam Al¹,Mukta Md. Saddam Hossain¹^ORCID,Saikat Md. Sezan Mahmud¹,Hossain Md. Ismail²,Islam Md. Adnanul³^ORCID,Ahmed Mohiuddin⁴^ORCID,Azam Sami⁵^ORCID

Affiliation:

1. Department of Computer Science and Engineering, United International University (UIU), Dhaka, Bangladesh

2. Department of Computer Science and Engineering, North South University, Dhaka, Bangladesh

3. Department of Human-Centered Computing (HCC), Action Lab, Monash University, Clayton, VIC, Australia

4. School of Science, Edith Cowan University, Joondalup, WA, Australia

5. College of Engineering and IT, Charles Darwin University, Casuarina, NT, Australia

Funder

Institute for Advanced Research Publication Grant of United International University, Bangladesh

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/09991956.pdf?arnumber=9991956

Reference54 articles.

1. Predictive Modelling of Susceptibility to Substance Abuse, Mortality and Drug-Drug Interactions in Opioid Patients

2. Using machine learning to predict opioid misuse among U.S. adolescents

3. Artificial intelligence in healthcare

4. Predictors of transition to heroin use among initially non-opioid dependent illicit pharmaceutical opioid users: A natural history study

5. Opioid Use after Radical Prostatectomy: Nationwide, Population Based Study in Sweden

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