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  "Title": "Network-Guided Temporal Forests for Feature Selection in\nHigh-Dimensional Longitudinal Data",
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  "Description": "Implements the Temporal Forest algorithm for feature\nselection in high-dimensional longitudinal data. The method\ncombines time-aware network construction via weighted gene\nco-expression network analysis (WGCNA), module-based feature\nscreening, and stability selection using tree-based models.\nThis package provides tools for reproducible longitudinal\nanalysis, closely following the methodology described in Shao,\nMoore, and Ramirez (2025)\n<https://github.com/SisiShao/TemporalForest>.",
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