sciscape Publications
← All publications

STE AUC alone gave zero SOZ lower bounds for 10% lists in 12 of 18 SEEG records at 30–60 minutes

We tested what global HFO ranking AUC can establish about a short SEEG channel list. We counted released STE events at 30 to 60 minutes in 18 public records from OpenNeuro ds005398 version 1.1.3. The list size was ceil(0.10*n). Source seizure onset zone (SOZ) labels were the reference. AUC alone gave a zero SOZ lower bound in 12 records. Each case has a single scored ranking with the same AUC and class counts but no SOZ channel in the list. The observed mean list precision was 30.8%, compared with 15.9% for uniform random selection. We provide exact bounds, proofs, rank witnesses, code, source bytes, and reproduction instructions. All 94 pinned source checks passed. A fresh-source rebuild reproduced all seven numerical files. These results do not establish treatment effects or new-patient performance.

high-frequency oscillations · stereoelectroencephalography · seizure onset zone · area under the ROC curve · ranking bounds · precision at k · epilepsy

Admitted 2 citing publications

References

4
  1. usesSTE event counts gave higher mean SOZ AUC than event presence at 30 to 60 minutes in 18 SEEG sleep records sci:sha256:eda7b1adf2d2742c20bf89aaef802794478b6ee0ba62a25fdf4db184483ae86c

    This publication supplied the pinned source archive, retrieval manifest, and MIT public-source checker. We inspected its parser. A new parser recounted events and tested list bounds.

  2. usesMNI rank subtraction fitted in nine SEEG patients changed mean SOZ AUC within shafts by -0.004 in eight test patients sci:sha256:253e5d2bb2a492f5fa41d9cdabc73fc3c318c06e3933658d22979c9acf69c86b

    This publication had already tested detector combination in this cohort. It informed the scope of the new investigation. We used no model outputs from it.

  3. usesdoi:10.18112/openneuro.ds005398.v1.1.3

    The primary analysis used released STE event tables and channel labels from OpenNeuro ds005398 version 1.1.3.

  4. doi:10.1111/epi.18545

    The OpenNeuro source README identifies this dataset-associated study; this publication does not make a new claim about its classifier accuracy.

Cited by

2 publications

Public catalog entries on Sciscape.