An Ensemble Deep Learning Approach for Sleep Stage Classification via Single-channel EEG and EOG. - In-Nea Wang; Choel-Hui Lee; Hyun-Ji Kim; Hakseung Kim; Dong-Joo Kim (ICTC, 2020)

Lateralization of alpha oscillation under preparation Lead to Efficiency of Motor Imagery: Related with Performance of Classification. - Seho Lee; Choel-Hui Lee; Hakseung Kim; Dong-Joo Kim (SMC, 2020)

Improving Sleep Stage Classification Performance by Single-Channel EEG Data Augmentation via Spectral Band Blending. - Choel-Hui Lee; Hyun-Ji Kim; Jae-Wook Heo; Hakseung Kim; Dong-Joo Kim (BCI, 2021)

EEG-Based Multioutput Classification of Sleep Stage and Apnea Using Deep Learning. - Donghyeok Jo; Choel-Hui Lee; Hakseung Kim; Hayom Kim; Jung-Bin Kim; Dong-Joo Kim (BCI, 2023)

SleepExpertNet: high-performance and class-balanced deep learning approach inspired from the expert neurologists for sleep stage classification. - Choel-Hui Lee; Hyun-Ji Kim; Young-Tak Kim; Hakseung Kim; Jung-Bin Kim; Dong-Joo Kim (J. Ambient Intell. Humaniz. Comput., 2023)

Correction to: SleepExpertNet: high‑performance and class‑balanced deep learning approach inspired from the expert neurologists for sleep stage classification. - Choel-Hui Lee; Hyun-Ji Kim; Young-Tak Kim; Hakseung Kim; Jung-Bin Kim; Dong-Joo Kim (J. Ambient Intell. Humaniz. Comput., 2023)

Negative-Sample-Free Contrastive Self-Supervised Learning for Electroencephalogram-Based Motor Imagery Classification. - In-Nea Wang; Choel-Hui Lee; Hakseung Kim; Dong-Joo Kim (IEEE Access, 2024)

Detection of Alzheimer's Disease and Frontotemporal Dementia: An Explainable Machine Learning Approach Using EEG Signals. - Hwa-Yeon Lee; Min-Kyung Jung; Choel-Hui Lee; Hakseung Kim; Dong-Joo Kim (BCI, 2025)

NeuroXAI: Adaptive, robust, explainable surrogate framework for determination of channel importance in EEG application. - Choel-Hui Lee; Daesun Ahn; Hakseung Kim; Eun Jin Ha; Jung-Bin Kim; Dong-Joo Kim (Expert Syst. Appl., 2025)