Mastodawn

while i enjoy algorithm development, data analysis, and programming, i am really glad that this study is almost over! so exciting to not feel like i'm chained to my desk for months at a time :) we currently compute two shape-feature distributions per electrographic waveform, yielding a total of 8 feature spaces for this 4-channel dataset. here is a montage showing the top-ranked ROI from each feature space! i fixed all hyperparameters except one, red outline shows top-ranked ROIs.

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katch wreck

corresponding training & test AUC-ROCs after reducing per-shapetype 1D Bayes classifier predictions to per-channel ROI predictions (reduction via a logical heuristic). each electrode position corresponds to a color code. red & green are contralateral to the trauma (brain lesion). yellow & black are ipsiperilesional. errorbars indicate 95% confidence intervals (jackknife estimate). holdout test partition came from the epileptogenic epoch (Day 1-7 post-TBI), training partition ~6 months post-TBI