Automated Annotation of Epileptiform Burden and Its Association with Outcomes.

Sahar F Zafar Eric S RosenthalJin JingWendong GeMohammad TabaeizadehHassan Aboul Nour Maryum ShoukatHaoqi SunFarrukh JavedSolomon KassaMuhammad EdhiElahe BordbarJustin GallagherValdery MouraManohar GhantaYu-Ping ShaoSungtae AnJimeng SunAndrew J Cole Michael Brandon Westover

Published in: Annals of neurology (2021)

Automated measurement of peak epileptiform activity burden affords a convenient, consistent, and quantifiable target for future multicenter randomized trials investigating whether suppressing epileptiform activity improves outcomes. ANN NEUROL 2021;90:300-311.

Keyphrases

machine learning
deep learning
high throughput
signaling pathway
risk factors
current status
metabolic syndrome
clinical trial