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Fig. 5 | BMC Medical Informatics and Decision Making

Fig. 5

From: A narrative review of the use of PROMs and machine learning to impact value-based clinical decision-making

Fig. 5

Key PROMs and ML techniques in studies of spinal condition patients. (A) PROMs that studies identified as outcomes of interest (B) PROMs which studies identified as significant outcome predictors (C) ML techniques that studies highlighted as best performing when more than one ML technique was investigated. Core Outcome Measures lndex (COMI), EuroQoL 5-Dimension (EQ-5D), Generalised Linear Mixed Model (GLMM), Hospital Anxiety and Depression Scale (HADS), Japanese Orthopedic Association Back Pain Evaluation Questionnaire (JOABPEQ), modified Japanese Orthopedic Association scale (mJOA), Modified Somatic Perception Questionnaire (MSPQ), Multivariate Adaptive Regression Splines (MuARS), Neck Disability Index (NDI), Oswestry Disability Index (ODI), Pain Catastrophizing Scale (PCS), Random Forest (RF), Self Efficacy Scale (SES), Short Form (SF), Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost)

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