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Template repo for Data Science for Biomedical Informatics (BMIN503/EPID600) final project

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BMIN503/EPID600 Final Project (DUE DATE FOR FINAL VERSION: 12/13/24 11:59PM)

[Overview] This project is to develop a predictive model for identifying opioid use disorder among chronic pain patients on long-term opioid therapy by incorporating diverse risk factors, grounded in the biopsychosocial model of pain. It provides a robust predictive framework and serves as a foundation for more advanced machine learning models that will incorporate a broader range of psychiatric conditions, ultimately enhancing early identification and intervention strategies for at-risk patients. For this project, I worked with two psychology experts who are specialized in substance use disorders, including opioid use disorder (Martin D. Cheatle, Associate Professor (Department of Psychiatry and Anesthesiology, Perelman School of Medicine) and Dr. Christal N. Davis, Postdoctoral researcher (Mental Illness Research, Education, and Clinical Center/ Department of Psychiatry and Anesthesiology, Perelman School of Medicine)

[Files] This Github repository includes this README, final_project_Lee.html, and final_project_Lee.qmd.

[Instruction] Please paste this URL: 'https://github.com/yoonjae-hub/BMIN503_Final_Project/blob/master/final_project_Lee.html' into the following website: https://htmlpreview.github.io/.

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Template repo for Data Science for Biomedical Informatics (BMIN503/EPID600) final project

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