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    Data_Sheet_1_Empiric Methods to Account for Pre-analytical Variability in Digital Histopathology in Frontotemporal Lobar Degeneration.docx by Lucia A. A. Giannini (6906953)

    Published 2019
    “…First, random iterations (×100) of linear regression showed that smaller training sets (N = 12–24), feasible for prospective use, have acceptable transformation prerequisites (mean Rsq: FTLD-Tau ≥0.9; FTLD-TDP ≥0.7). When cross-validated on independent complementary testing sets, in FTLD-Tau, N = 12 training sets resulted in 100% of GM and WM transformations with optimal transformation outcomes (ICC ≥ 0.8), while in FTLD-TDP N = 24 training sets resulted in optimal ICC in testing sets (GM = 72%, WM = 98%). …”