Jung-Gu Choi

According to our database, Jung-Gu Choi authored at least 8 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Early-stage detection of cognitive impairment by hybrid quantum-classical algorithm using resting-state functional MRI time-series.

Junggu Choi, Tak Hur, Daniel K. Park, Na-Young Shin, Seung-Koo Lee, Hakbae Lee, Sanghoon Han

CoRR, 2024

Association between Prefrontal fNIRS signals during Cognitive tasks and College scholastic ability test (CSAT) scores: Analysis using a quantum annealing approach.

Yeaju Kim, Jung-Gu Choi, Bora Kim, Yongwan Park, Jihyun Cha, Jongkwan Choi, Sanghoon Han

CoRR, 2024

2023

Investigation of factors regarding the effects of COVID-19 pandemic on college students' depression by quantum annealer.

Jung-Gu Choi, Kion Kim, Soohyun Park, Juyoen Hur, Hyunjung Yang, Younghoon Kim, Hakbae Lee, Sanghoon Han

CoRR, 2023

2022

Interpretable Fusion Analytics Framework for fMRI Connectivity: Self-Attention Mechanism and Latent Space Item-Response Model.

Jeong-Jae Kim, Yeseul Jeon, Sumin Yu, Jung-Gu Choi, Sanghoon Han

CoRR, 2022

Machine Learning Approach for Classifying College Scholastic Ability Test Levels With Unsupervised Features From Prefrontal Functional Near-Infrared Spectroscopy Signals.

Jung-Gu Choi, Inhwan Ko, Yoonjin Nah, Bora Kim, Yongwan Park, Jihyun Cha, Jongkwan Choi, Sanghoon Han

IEEE Access, 2022

2021

Deep Learning Approach to Generate a Synthetic Cognitive Psychology Behavioral Dataset.

Jung-Gu Choi, Yoonjin Nah, Inhwan Ko, Sanghoon Han

IEEE Access, 2021

Machine Learning Framework for Multi-Level Classification of Company Revenue.

Jung-Gu Choi, Inhwan Ko, Jeong-Jae Kim, Yeseul Jeon, Sanghoon Han

IEEE Access, 2021

Depression Level Classification Using Machine Learning Classifiers Based on Actigraphy Data.

Jung-Gu Choi, Inhwan Ko, Sanghoon Han

IEEE Access, 2021