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. 2024 Sep 14;7(3):ooae084. doi: 10.1093/jamiaopen/ooae084

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© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

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Graphs summarizing the simulation results under the scenario of 1:19 case-control ratio, showing that PheW2P2V outperforms all baseline methods, especially when signals are weak. — Simulation results of medians, 25th and 75th percentiles of AUC-ROC, max F₁-score, and AUC-PR of the proposed PheW²P2V, the LASSO regression, the random forest classifier, the gradient boosted tree classifier, and the unweighted version P2V with regression coefficient $β$ ranges from 0.2 to 0.8, under the scenario of 1:19 case-control ratio.