Fig. 3: Performance of cognitive decline prediction using different pathology models across cross-validation repetitions. | Communications Medicine

Fig. 3: Performance of cognitive decline prediction using different pathology models across cross-validation repetitions.

From: Integrating individualized connectome with amyloid pathology improves predictive modeling of future cognitive decline

Fig. 3

a Distributions of differences in correlation coefficients between predicted and actual cognitive decline scores across different pathology models. Prediction performance was compared across cross-validation repetitions with the regional standardized uptake value ratio (SUVR) model as the reference. Incorporating structural connectome (SC) with connectivity-weighted network-based amyloid-β pathology (NAP) achieved the highest performance, and outperformed the prediction performance of regional SUVR measures. b Comparison of the ratio of root mean squared error (RMSE) performance between pathology models. Compared to regional SUVR measures, connectivity-weighted NAP measure of SC had smaller RMSE, whereas connectivity-weighted NAP measures of functional connectome (FC) had higher RMSE. The analysis included seventy-seven participants for whom all data were available.

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