Chronic pain, affecting approximately 30% of the global population, presents complex challenges of physical discomfort accompanied with psychological distress. Current treatments involve a combination of practices such as lifestyle adjustments, opioid and non-opioid pharmacological therapies, psychological interventions, and integrative treatments. This project investigates the efficacy of Mindfulness-Based Stress Reduction (MBSR) in chronic pain management, with a focus on MBSR’s role in modulating pain perception and functional improvement. Leveraging machine learning techniques, including Random Forest, XGBoost, and Decision Trees, this study delves into feature importance analysis for both classification and regression models to discern the key factors influencing treatment outcomes. The findings aspire to contribute to the nuanced understanding of pain treatment, potentially guiding future interventions towards more personalized and effective pain management strategies.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Evans, Adeline

Subject

• Health
• Well-Being
• Computing

Publisher

• Worcester Polytechnic Institute

Identifier

• 119171
• E-project-032224-152221

Mot-clé

• Machine Learning
• Mindfulness
• Chronic Pain

Advisor

• Nephew, Benjamin
• Ruiz, Carolina

Year

• 2024

Date created

• 2024-03-22

Resource type

• Major Qualifying Project

Major

• Computer Science

Source

• E-project-032224-152221

Rights statement

• In Copyright