Profiling Arthritis Pain with a Decision Tree

ConclusionPhysical and mental function scores, the ability to climb stairs, and overall assessment of feeling were the most discriminative predictors from the 12 identified variables, predicting pain with 86% accuracy for individuals with arthritis. In this era of rapid expansion of big data application, the nature of healthcare research is moving from hypothesis‐driven to data‐driven solutions. The algorithms generated in this study offer new insights on individualized pain prediction, allowing the development of cost‐effective care management programs for those experiencing arthritis pain.

Source: Pain Practice - November 20, 2017 Category: Anesthesiology Authors: Man Hung, Jerry Bounsanga, Fangzhou Liu, Maren W. Voss Tags: Original Article Source Type: research