Seung-Hwan Lee

Professor

Inje University Ilsan Paik Hospital

South Korea

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About

Seung-Hwan Lee is a Professor at Inje University Ilsan Paik Hospital in South Korea. His research focuses on the application of electroencephalography and machine learning in diagnosing and predicting treatment responses for psychiatric disorders, including posttraumatic stress disorder and major depressive disorder. Recent publications highlight his contributions to understanding brain connectivity and the clinical implications of neuropsychiatric treatments.

Articles (17)

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2025

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2025

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2025

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2025

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2025

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2024

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2023

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2023

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2023

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2023

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2023

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2023

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2023

Collaborators (4)

Min Jin Jin

Kongju National University

SOUTH KOREA

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Woojae Myung

Seoul National University Hospital

SOUTH KOREA

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Han-Jeong Hwang

Assistant Professor

Sejong University

SOUTH KOREA

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Sunkyung Yoon

Assistant professor

Sungkyunkwan University

SOUTH KOREA

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Seung-Hwan Lee

Research Interests

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About

Articles (17)

Enhancing Electroencephalogram-Based Prediction of Posttraumatic Stress Disorder Treatment Response Using Data Augmentation

Predicting antidepressant responsiveness in major depressive disorder patients via electroencephalography gamma-band dynamic functional connectivity in response to salient auditory stimuli

Machine learning-based differentiation of schizophrenia and bipolar disorder using multiscale fuzzy entropy and relative power from resting-state EEG

Layer‐Wise Relevance Propagation Approach for Diagnosis of Drug‐Naïve Men With Major Depressive Disorder Using Resting‐State Electroencephalography

Association between the functional brain network and antidepressant responsiveness in patients with major depressive disorders: a resting-state EEG study

Clinical Implication of Maumgyeol Basic Biotypes–Electroencephalography- and Photoplethysmogram-Based Bwave State Inventory

Functional Near‐Infrared Spectroscopy‐Based Computer‐Aided Diagnosis of Major Depressive Disorder Using Convolutional Neural Network with a New Channel Embedding Layer Considering Inter‐Hemispheric Asymmetry in Prefrontal Hemodynamic Responses

Transcranial Electrical Stimulation: Clinical Implication and Practice for Treatment of Psychiatric Illness

Clinical Implication of Maumgyeol Basic Service–the 2 Channel Electroencephalography and a Photoplethysmogram–based Mental Health Evaluation Software

The Role of Glutamate Underlying Treatment-resistant Depression

Vagus Nerves Stimulation: Clinical Implication and Practical Issue as a Neuropsychiatric Treatment

Effect of Home-based Self-administered Transcranial Direct Stimulation in Patients with Mild to Moderate Major Depressive Disorder: A Single-arm, Multicentral Trial

Inflammatory Markers and Brain Volume in Patients with Post-traumatic Stress Disorder

The Importance of Low-frequency Alpha (8−10 Hz) Waves and Default Mode Network in Behavioral Inhibition

Relationship Between Loudness Dependence of Auditory-evoked Potentials and Suicidality

Electroceutical and Bioelectric Therapy: Its Advantages and Limitations

Automatic Depression Detection Using Smartphone-Based Text-Dependent Speech Signals: Deep Convolutional Neural Network Approach

Collaborators (4)

Min Jin Jin

Woojae Myung

Han-Jeong Hwang

Sunkyung Yoon

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