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Beom-Sok Jung

Korea Advanced Institute of Science and Technology · Medicine

About the Lab

Professor Beom-Sok Jung's research lab specializes in computational and neuroimaging approaches to understand brain-behavior relationships in neuropsychiatric and neurodegenerative disorders. The lab focuses on applying advanced neuroimaging techniques—such as perfusion MRI, diffusion tensor imaging (DTI), and functional MRI—combined with machine learning and multivariate statistical models to investigate functional and structural brain abnormalities in conditions like depression, schizophrenia, ADHD, Alzheimer’s disease, and Internet Gaming Disorder. A key research direction involves developing interpretable AI models to predict disease phenotypes from brain imaging data, with translational goals in early detection, biomarker discovery, and personalized intervention strategies.

neuroimagingmachine learningbrain connectivitymental healthneurodegenerative disease

Research Overview

Papers
124
Total Citations
2,650
Papers (5y)
20
Primary Field
Medicine

Research Output Trend

Figures are computed from collected data and may differ slightly.

Publications per year (5y)
20total
2022
2023
2024
2025
2026
Citations per year (5y)
35total
20222023202420252026

Selected Papers

15
1
Article|130 citations·2013
Activities on Facebook Reveal the Depressive State of Users
Sungkyu Park, Sang Won Lee, Jinah Kwak, Meeyoung Cha, Bumseok Jeong
SJR Q1Journal of Medical Internet ResearchOA

Our results using EmotionDiary demonstrated that the more depressed one is, the more one will read tips and facts about depression. We also confirmed depressed individuals had significantly fewer interactions with others (eg, decreased number of friends and location tagging). Our app, EmotionDiary, can successfully evaluate depressive symptoms as well as provide useful tips and facts to users. These results open the door for examining Facebook activities to identify depressed individuals. We aim

Social PsychologyPsychology
2
Article|119 citations·2019
Prediction of IDH genotype in gliomas with dynamic susceptibility contrast perfusion MR imaging using an explainable recurrent neural network
Kyu Sung Choi, Seung Hong Choi, Bumseok Jeong
SJR Q1Neuro-OncologyOA

BACKGROUND: The aim of this study was to predict isocitrate dehydrogenase (IDH) genotypes of gliomas using an interpretable deep learning application for dynamic susceptibility contrast (DSC) perfusion MRI. METHODS: Four hundred sixty-three patients with gliomas who underwent preoperative MRI were enrolled in the study. All the patients had immunohistopathologic diagnoses of either IDH-wildtype or IDH-mutant gliomas. Tumor subregions were segmented using a convolutional neural network followed b

GeneticsMedicine
3
Article|116 citations·2009
Functional and anatomical connectivity abnormalities in left inferior frontal gyrus in schizophrenia
Bumseok Jeong, Cynthia G. Wible, Ryuichiro Hashimoto, Marek Kubicki
SJR Q1Human Brain MappingOA

Functional studies in schizophrenia demonstrate prominent abnormalities within the left inferior frontal gyrus (IFG) and also suggest the functional connectivity abnormalities in language network including left IFG and superior temporal gyrus during semantic processing. White matter connections between regions involved in the semantic network have also been indicated in schizophrenia. However, an association between functional and anatomical connectivity disruptions within the semantic network i

Radiology, Nuclear Medicine and ImagingMedicine
4
Article|108 citations·2015
Ultrasound stimulation inhibits recurrent seizures and improves behavioral outcome in an experimental model of mesial temporal lobe epilepsy
Hilola Hakimova, Sang‐Woo Kim, Kon Chu, Sang Kun Lee, Bumseok Jeong, Daejong Jeon
SJR Q2Epilepsy & Behavior
Biomedical EngineeringEngineering
5
Article|63 citations·2013
Aberrant Development of Functional Connectivity among Resting State-Related Functional Networks in Medication-Naïve ADHD Children
Jeewook Choi, Bumseok Jeong, Sang Won Lee, Hyo-Jin Go
SJR Q1PLoS ONEOA

Our results suggest that medication-naïve ADHD subjects may have delayed maturation of the two functional connections, SN-Sensory/Motor and aDMN-pDMN/prec. Interventions that enhance the functional connectivity of these two connections may merit attention as potential therapeutic or preventive options in both ADHD and TDC.

Cognitive NeuroscienceNeuroscience
6
Article|51 citations·2017
Predicting neurocognitive function with hippocampal volumes and DTI metrics in patients with Alzheimer's dementia and mild cognitive impairment
Geumsook Shim, Kwang‐Yeon Choi, Dohyun Kim, Sang‐il Suh, Suji Lee, Hyun‐Ghang Jeong, Bumseok Jeong
SJR Q2Brain and BehaviorOA

INTRODUCTION: Cognitive performance in patients with Alzheimer's dementia (AD) and mild cognitive impairment (MCI) has been reported to be related to hippocampal atrophy and microstructural changes in white matter (WM). We aimed to predict the neurocognitive functions of patients with MCI or AD using hippocampal volumes and diffusion tensor imaging (DTI) metrics via partial least squares regression (PLSR). METHODS: = 33). Twenty-four hippocampal subfield volumes and the average values for fracti

Psychiatry and Mental healthMedicine
7
Article|40 citations·2016
Insights from an expressive writing intervention on Facebook to help alleviate depressive symptoms
Sang Won Lee, Inyeop Kim, Jaehyun Yoo, Sungkyu Park, Bumseok Jeong, Meeyoung Cha
SJR Q1Computers in Human Behavior
Social PsychologyPsychology
8
Article|40 citations·2015
White matter connectivity and Internet gaming disorder
Bumseok Jeong, Doug Hyun Han, Sun Mi Kim, Sang Won Lee, Perry F. Renshaw
SJR Q1Addiction BiologyOA

Internet use and on-line game play stimulate corticostriatal-limbic circuitry in both healthy subjects and subjects with Internet gaming disorder (IGD). We hypothesized that increased fractional anisotropy (FA) with decreased radial diffusivity (RD) would be observed in IGD subjects, compared with healthy control subjects, and that these white matter indices would be associated with clinical variables including duration of illness and executive function. We screened 181 male patients in order to

Cognitive NeuroscienceNeuroscience
9
Article|38 citations·2010
Reduced task-related suppression during semantic repetition priming in schizophrenia
Bumseok Jeong, Marek Kubicki
SJR Q1Psychiatry Research Neuroimaging
Cognitive NeuroscienceNeuroscience
10
Article|35 citations·2020
Data-driven analysis using multiple self-report questionnaires to identify college students at high risk of depressive disorder
Bongjae Choi, Geumsook Shim, Bumseok Jeong, Sungho Jo
SJR Q1Scientific ReportsOA

Depression diagnosis is one of the most important issues in psychiatry. Depression is a complicated mental illness that varies in symptoms and requires patient cooperation. In the present study, we demonstrated a novel data-driven attempt to diagnose depressive disorder based on clinical questionnaires. It includes deep learning, multi-modal representation, and interpretability to overcome the limitations of the data-driven approach in clinical application. We implemented a shared representation

Experimental and Cognitive PsychologyPsychology
11
Article|33 citations·2019
Exploring characteristic features of attention-deficit/hyperactivity disorder: findings from multi-modal MRI and candidate genetic data
Jae Hyun Yoo, Johanna Inhyang Kim, Bung-Nyun Kim, Bumseok Jeong
SJR Q1Brain Imaging and Behavior
Psychiatry and Mental healthMedicine
12
Article|32 citations·2005
Functional imaging evidence of the relationship between recurrent psychotic episodes and neurodegenerative course in schizophrenia
Bumseok Jeong, Jun Soo Kwon, Seong Yoon Kim, Chul Lee, Tak Youn, Chan‐Hong Moon, Chang Yoon Kim
SJR Q1Psychiatry Research Neuroimaging
Radiology, Nuclear Medicine and ImagingMedicine
13
Article|32 citations·2015
Aberrant function of frontoamygdala circuits in adolescents with previous verbal abuse experiences
Sang Won Lee, Jae Hyun Yoo, Ko Woon Kim, Jong-Sun Lee, Dongchan Kim, Hyunwook Park, Jeewook Choi, Bumseok Jeong
SJR Q2Neuropsychologia
Clinical PsychologyPsychology
14
Article|25 citations·2017
The effects of GRIN2B and DRD4 gene variants on local functional connectivity in attention-deficit/hyperactivity disorder
Johanna Inhyang Kim, Jae Hyun Yoo, Dohyun Kim, Bumseok Jeong, Bung-Nyun Kim
SJR Q1Brain Imaging and Behavior
Psychiatry and Mental healthMedicine
15
Article|24 citations·2021
Deep graph neural network-based prediction of acute suicidal ideation in young adults
Kyu Sung Choi, Sunghwan Kim, Byung-Hoon Kim, Hong Jin Jeon, Jong‐Hoon Kim, Joon Hwan Jang, Bumseok Jeong
SJR Q1Scientific ReportsOA

Precise remote evaluation of both suicide risk and psychiatric disorders is critical for suicide prevention as well as for psychiatric well-being. Using questionnaires is an alternative to labor-intensive diagnostic interviews in a large general population, but previous models for predicting suicide attempts suffered from low sensitivity. We developed and validated a deep graph neural network model that increased the prediction sensitivity of suicide risk in young adults (n = 17,482 for training

Clinical PsychologyPsychology

Research Areas

Cognitive NeurosciencePsychiatry and Mental healthClinical PsychologyExperimental and Cognitive PsychologySociology and Political ScienceRadiology, Nuclear Medicine and Imaging

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