Výsledky vyhledávání - "Hee Seok Song"

Akademický článek

Early Prediction of Cardiac Arrest in the Intensive Care Unit Using Explainable Machine Learning: Retrospective Study

Autor: Yun Kwan Kim, Won-Doo Seo, Sun Jung Lee, Ja Hyung Koo, Gyung Chul Kim, Hee Seok Song, Minji Lee

Publikováno v: Journal of Medical Internet Research, Vol 26, p e62890 (2024)

BackgroundCardiac arrest (CA) is one of the leading causes of death among patients in the intensive care unit (ICU). Although many CA prediction models with high sensitivity have been developed to anticipate CA, their practical application has been c

Externí odkaz: https://doaj.org/article/d176d3470a9d4fc8acc69ac147499374

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Akademický článek

Explainable Artificial Intelligence Warning Model Using an Ensemble Approach for In-Hospital Cardiac Arrest Prediction: Retrospective Cohort Study

Autor: Yun Kwan Kim, Ja Hyung Koo, Sun Jung Lee, Hee Seok Song, Minji Lee

Publikováno v: Journal of Medical Internet Research, Vol 25, p e48244 (2023)

BackgroundCardiac arrest (CA) is the leading cause of death in critically ill patients. Clinical research has shown that early identification of CA reduces mortality. Algorithms capable of predicting CA with high sensitivity have been developed using

Externí odkaz: https://doaj.org/article/6a95281eed4d41de9b922f4d82268072

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Akademický článek

Enhanced thermal diffusion in the vertical direction of flexible polyimide composite films with magnetically alignable h-BN platelets via ferrofluids hybridization

Autor: Hee Seok Song, Chanil Park, Youn-Sang Bae, Yong Seok Kim, Ho Sun Lim, Youngjae Yoo

Publikováno v: Journal of Materials Research and Technology, Vol 20, Iss , Pp 2921-2930 (2022)

A facile approach is proposed to improve the anisotropic heat conduction of polyimide composite films containing hexagonal boron nitride (h-BN), thermally conductive filler with high anisotropy, via surface hybridization with ferrofluids as magnetic

Externí odkaz: https://doaj.org/article/fc555b751c8b489f8a9c6e5bed5313a5

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Explainable AI Warning Model Using Ensemble Approach for In-Hospital Cardiac Arrest Prediction: A Retrospective Cohort Study (Preprint)

Autor: Yun Kwan Kim, Ja Hyung Koo, Sun Jung Lee, Hee Seok Song, Minji Lee

BACKGROUND Cardiac arrest (CA) is the leading cause of death in critically ill patients, and clinical research has shown that the early identification of CA reduces mortality. Algorithms capable of predicting CA through multivariate time-series data

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4b066332a1e7be8dd00650a7aeddd730
https://doi.org/10.2196/preprints.48244

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Three-day monitoring of adhesive single-lead electrocardiogram patch for premature ventricular complex: validation of diagnostic yield and evaluation of burden fluctuation (Preprint)

Autor: Hyo-Jeong Ahn, Eue-Keun Choi, Soonil Kwon, So-Ryoung Lee, Hee-Seok Song, Young-Shin Lee, Seil Oh

BACKGROUND Wearable monitoring devices of an electrocardiogram (ECG) are widely used. However, the date of an adhesive single-lead ECG patch (SEP) in the diagnosis and 24-hour burden assessment of premature ventricular complex (PVC) is limited. OBJEC

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::59d1285fb2bc103150ffa65b208cd8fb
https://doi.org/10.2196/preprints.46098

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Comparison Between the 24-hour Holter Test and 72-hour Single-Lead Electrocardiogram Monitoring With an Adhesive Patch-Type Device for Atrial Fibrillation Detection: Prospective Cohort Study (Preprint)

Autor: Soonil Kwon, So-Ryoung Lee, Eue-Keun Choi, Hyo-Jeong Ahn, Hee-Seok Song, Young-Shin Lee, Seil Oh, Gregory Y H Lip

BACKGROUND There is insufficient evidence for the use of single-lead electrocardiogram (ECG) monitoring with an adhesive patch-type device (APD) over an extended period compared to that of the 24-hour Holter test for atrial fibrillation (AF) detectio

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::000c5af6330c81f364a112ef117e2e80
https://doi.org/10.2196/preprints.37970

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