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Cardiology / Original Article
Enhanced prediction of left ventricular ejection fraction using electrocardiography with the addition of clinical metadata
Hyun Woong Park, Taeseen Kang, Young-Hoon Seo, Jae-Hyeong Park
Korean J Intern Med. 2026;41(1):118-130. Published online January 1, 2026
Background/Aims: Left ventricular ejection fraction (LVEF) is a key echocardiographic parameter for assessing LV systolic function, guiding the management of many cardiovascular diseases, including heart failure (HF). While traditional electrocardiography (ECG) has been widely used in clinical pract..
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Cardiology / Original Article
Automatic quantitative analysis of atherosclerotic aortic plaques in patients with embolic cerebral infarction using deep learning
Hye Jin Bang, Jae-Hyeong Park, Sun Geu Chae, Suk Joo Bae, Ji-Hoon Jung, You Hee Cho, Jong Won Park, Dae-Won Kim, Jung Sun Cho
Korean J Intern Med. 2025;40(5):767-779. Published online August 26, 2025
Background/Aims: Transesophageal echocardiography (TEE) is a commonly used imaging modality for assessing embolic stroke of undetermined source (ESUS) in clinical practice. We aimed to develop an automatic plaque segmentation model based on U-net and evaluate its clinical usefulness in patients with..
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Cardiology / Original Article
Explainable paroxysmal atrial fibrillation diagnosis using an artificial intelligence-enabled electrocardiogram
Yeongbong Jin, Bonggyun Ko, Woojin Chang, Kang-Ho Choi, Ki Hong Lee
Korean J Intern Med. 2025;40(2):251-261. Published online February 21, 2025
Background/Aims: Atrial fibrillation (AF) significantly contributes to global morbidity and mortality. Paroxysmal atrial fibrillation (PAF) is particularly common among patients with cryptogenic strokes or transient ischemic attacks and has a silent nature. This study aims to develop reliable artifi..
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Nephrology / Review
Machine learning approaches toward an understanding of acute kidney injury: current trends and future directions
Inyong Jeong, Nam-Jun Cho, Se-Jin Ahn, Hwamin Lee, Hyo-Wook Gil
Korean J Intern Med. 2024;39(6):882-897. Published online October 29, 2024
Acute kidney injury (AKI) is a significant health challenge associated with adverse patient outcomes and substantial economic burdens. Many authors have sought to prevent and predict AKI. Here, we comprehensively review recent advances in the use of artificial intelligence (AI) to predict AKI, and t..
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Gastroenterology / Review
Artificial intelligence in colonoscopy: from detection to diagnosis
Eun Sun Kim, Kwang-Sig Lee
Korean J Intern Med. 2024;39(4):555-562. Published online May 2, 2024
This study reviews the recent progress of artificial intelligence for colonoscopy from detection to diagnosis. The source of data was 27 original studies in PubMed. The search terms were “colonoscopy” (title) and “deep learning” (abstract). The eligibility criteria were: (1) the dependent varia..
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