EPICv2 thyroid classifiers: invasiveness and driver group (CCR 2026), methscope random forests
Wanding Zhou
4baddd9
EPICv2_thyroid_invasiveness.clfx (High/Low) and EPICv2_thyroid_driver.clfx
(BRAF V600E, DICER1, Kinase Fusion, Ras-like): the pediatric thyroid
carcinoma classifiers of Li et al. (CCR 2026) rebuilt with methscope's
random forest (classify-train --framework rf) on the 87 / 84 reference-
cohort primaries. Leave-one-out they match the published R forests (85.1%
vs 83.9%, 92.9% vs 95.2%); on the validation primaries 76.1% vs 75.0% and
80.5% vs 84.1%. Scored by a methscope with the rf framework.
SHA256SUMS adds the two files; README adds the EPICv2 fetch line.
