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Neurology
Big data analysis and artificial intelligence in epilepsy – common data model analysis and machine learning-based seizure detection and forecasting
Yoon Gi Chung, Yonghoon Jeon, Sooyoung Yoo, Hunmin Kim, Hee Hwang
Clin Exp Pediatr. 2022;65(6):272-282.   Published online November 26, 2021
· Big data analysis, such as common data model and artificial intelligence, can solve relevant questions and improve clinical care.
· Recent deep learning studies achieved 0.887–0.996 areas under the receiver operating characteristic curve for automated interictal epileptiform discharge detection.
· Recent deep learning studies achieved 62.3%–99.0% accuracy for interictal-ictal classification in seizure detection and 75.0%– 87.8% sensitivity with a 0.06–0.21/hr false positive rate in seizure forecasting.
Magnetoencephalography in pediatric epilepsy
Hunmin Kim, Chun Kee Chung, Hee Hwang
Clin Exp Pediatr. 2013;56(10):431-438.   Published online October 31, 2013

Magnetoencephalography (MEG) records the magnetic field generated by electrical activity of cortical neurons. The signal is not distorted or attenuated, and it is contactless recording that can be performed comfortably even for longer than an hour. It has excellent and decent temporal resolution, especially when it is combined with the patient's own brain magnetic resonance imaging (magnetic source imaging). Data...

Case Report
Hypokalemic periodic paralysis; two different genes responsible for similar clinical manifestations
Hunmin Kim, Hee Hwang, Hae Il Cheong, Hye Won Park
Clin Exp Pediatr. 2011;54(11):473-476.   Published online November 30, 2011

Primary hypokalemic periodic paralysis (HOKPP) is an autosomal dominant disorder manifesting as recurrent periodic flaccid paralysis and concomitant hypokalemia. HOKPP is divided into type 1 and type 2 based on the causative gene. Although 2 different ion channels have been identified as the molecular genetic cause of HOKPP, the clinical manifestations between the 2 groups are similar. We report the...

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