Fig. 5: Cluster prediction metrics and defining rules in the osteoarthritis (OA) study population (time-window between data collection at the assessment centre and OA diagnosis (any OA): less than 5 years) and validation in independent hold-out population (time-window: 5 to 11 years). | Nature Communications

Fig. 5: Cluster prediction metrics and defining rules in the osteoarthritis (OA) study population (time-window between data collection at the assessment centre and OA diagnosis (any OA): less than 5 years) and validation in independent hold-out population (time-window: 5 to 11 years).

From: Data-driven identification of predictive risk biomarkers for subgroups of osteoarthritis using interpretable machine learning

Fig. 5

Left (heatmap): each cluster is defined by prediction metrics, percentage of cases, cluster size (%). Middle (text): set of rules best defining each cluster, based on the model input values and generated by a decision tree model. Right (heatmap): percentages of cases and cluster size (%) in an independent population in which individuals were attributed to clusters according to their corresponding rules. OA osteoarthritis, NSAIDs non-steroidal anti-inflammatory steroid drugs, Avg Pred Prob average prediction probability per cluster, PPV Positive predictive value.

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