Joonghee Kim

Associate professor

Seoul National University Hospital

South Korea

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About

Joonghee Kim is an Associate Professor at Seoul National University Bundang Hospital in South Korea. His research areas include the application of artificial intelligence in electrocardiography, myocardial infarction detection, and assessment of gait speed. He has authored several recent articles focusing on the diagnostic performance of AI in cardiovascular conditions and the validation of electrocardiogram analysis in various clinical settings.

Articles (17)

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2025

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2020

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2020

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2020

Collaborators (24)

Young Taeck Oh

Clinical Assistant Professor

Hallym University Dongtan Sacred Heart Hospital

SOUTH KOREA

Joonghee Kim

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Articles (17)

Interethnic validation of electrocardiogram image analysis software for detecting left ventricular dysfunction in an emergency department population

AI-ECG Supported Decision-Making for Coronary Angiography in Acute Chest Pain: The QCG-AID Study

Minimum required distance for clinically significant measurement of habitual gait speed

Comparative Diagnostic Performance of a Multimodal Large Language Model Versus a Dedicated Electrocardiogram AI in Detecting Myocardial Infarction From Electrocardiogram Images: Comparative Study

Non-Inferiority Analysis of Electrocardiography Analysis Application vs. Point-of-Care Ultrasound for Screening Left Ventricular Dysfunction

Smartphone AI vs. Medical Experts: A Comparative Study in Prehospital STEMI Diagnosis

Lack of Fall Prevention Education in Patients Experiencing Fall-Related Hip Fracture: A Qualitative Study

Artificial Intelligence–Based Electrocardiographic Biomarker for Outcome Prediction in Patients With Acute Heart Failure: Prospective Cohort Study

Performance of ECG-Derived Digital Biomarker for Screening Coronary Occlusion in Resuscitated Out-of-Hospital Cardiac Arrest Patients: A Comparative Study between Artificial Intelligence and a Group of Experts

Feasibility of Artificial Intelligence–Based Electrocardiography Analysis for the Prediction of Obstructive Coronary Artery Disease in Patients With Stable Angina: Validation Study

Hyperkalemia Detection in Emergency Departments Using Initial ECGs: A Smartphone AI ECG Analyzer vs. Board-Certified Physicians

Impact of an Emergency Department Isolation Policy for Patients With Suspected COVID-19 on Door-to-Electrocardiography Time and Clinical Outcomes in Patients With Acute Myocardial Infarction

A Retrospective Clinical Evaluation of an Artificial Intelligence Screening Method for Early Detection of STEMI in the Emergency Department

Prediction of Neurological Outcomes in Out-of-hospital Cardiac Arrest Survivors Immediately after Return of Spontaneous Circulation: Ensemble Technique with Four Machine Learning Models.

Prolonged stay in the emergency department is an independent risk factor for hospital‐acquired pressure ulcer

Developing neural network models for early detection of cardiac arrest in emergency department

Factors associated with first-pass success of emergency endotracheal intubation

Collaborators (24)

Young Taeck Oh

Woon Yong Kwon

Taegyun Kim

You Hwan Jo

Inwon Park

Jaewon Beom

Seok-Min Kang

Yu Jin Kim

Dongbum Suh

Sumin Baek

Ji Hyun Lee

IL-YOUNG OH

Sun Chung

Dong Keon Lee

Seung Min Park

Hyunglan Chang

Youngjin Cho

Dong-Ju Choi

Kyoung Jun Song

Dong-Hyun Jang

JIN HEE LEE

Eunkyoung Lee

Yeonyee Yoon

Keewon Kim

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