Penalized landmark supermodels (penLM) for dynamic prediction for time-to-event outcomes in high-dimensional data by Anya H. Fries, Eunji Choi, Summer S. Han

“…When evaluated using the proposed metrics, the penLM model developed using multi-source data ( $$\:\overline{AUC}_{w}\:$$ of 0.77 [95% confidence interval: 0.74–0.79]) outperformed those developed using single-source data ( $$\:\overline{AUC}_{w}\:$$ range: 0.50–0.74). …”
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