Výsledky vyhledávání - "Sang Gil Han"

Akademický článek

Effect of deep learning-based assistive technology use on chest radiograph interpretation by emergency department physicians: a prospective interventional simulation-based study

Autor: Ji Hoon Kim, Sang Gil Han, Ara Cho, Hye Jung Shin, Song-Ee Baek

Publikováno v: BMC Medical Informatics and Decision Making, Vol 21, Iss 1, Pp 1-9 (2021)

Abstract Background Interpretation of chest radiographs (CRs) by emergency department (ED) physicians is inferior to that by radiologists. Recent studies have investigated the effect of deep learning-based assistive technology on CR interpretation (D

Externí odkaz: https://doaj.org/article/708f74a503d14da78185fd2464308dc7

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Akademický článek

Virtual reality-based neurological examination teaching tool(VRNET) versus standardized patient in teaching neurological examinations for the medical students: a randomized, single-blind study

Autor: Sang Gil Han, Young Dae Kim, Tae Young Kong, Junho Cho

Publikováno v: BMC Medical Education, Vol 21, Iss 1, Pp 1-8 (2021)

Abstract Background The conventional methods for teaching neurological examination with real patients to medical students have some limitations if the patient with the symptom or disease is not available. Therefore, we developed a Virtual Reality-bas

Externí odkaz: https://doaj.org/article/f3b3d187e72b4e61a4f39278743692ef

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Akademický článek

Differential Biases and Variabilities of Deep Learning–Based Artificial Intelligence and Human Experts in Clinical Diagnosis: Retrospective Cohort and Survey Study

Autor: Dongchul Cha, Chongwon Pae, Se A Lee, Gina Na, Young Kyun Hur, Ho Young Lee, A Ra Cho, Young Joon Cho, Sang Gil Han, Sung Huhn Kim, Jae Young Choi, Hae-Jeong Park

Publikováno v: JMIR Medical Informatics, Vol 9, Iss 12, p e33049 (2021)

BackgroundDeep learning (DL)–based artificial intelligence may have different diagnostic characteristics than human experts in medical diagnosis. As a data-driven knowledge system, heterogeneous population incidence in the clinical world is conside

Externí odkaz: https://doaj.org/article/4621df219b094013ac34c6e13d808523

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Emergency Department Return Prediction System Using Blood Samples With LightGBM for Smart Health Care Services

Autor: Hyun Soo Chung, Sangdo Kim, Younghwan Shin, Sang Gil Han, Jong-Moon Chung, Junho Cho

Publikováno v: IEEE Consumer Electronics Magazine. 10:42-48

This article proposes a novel Blood sample-based Emergency department (ED) Return (BER) scheme that predicts the ED return probability using LightGBM. In the proposed BER scheme, LightGBM makes predictions on ED return based on blood samples. Since b

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::eacfe763297573829ef97142d2741981
https://doi.org/10.1109/mce.2020.3015439

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Effect of deep learning-based assistive technology use on chest radiograph interpretation by emergency department physicians: a prospective interventional simulation-based study

Autor: Ara Cho, Ji Hoon Kim, Song-Ee Baek, Sang Gil Han, Hye Jung Shin

Publikováno v: BMC Medical Informatics and Decision Making, Vol 21, Iss 1, Pp 1-9 (2021)
BMC Medical Informatics and Decision Making

Background Interpretation of chest radiographs (CRs) by emergency department (ED) physicians is inferior to that by radiologists. Recent studies have investigated the effect of deep learning-based assistive technology on CR interpretation (DLCR), alt

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bf1ecf90b7fa6523f4f3fbff8fa43700
https://doi.org/10.1186/s12911-021-01679-4

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Virtual reality-based neurological examination teaching tool(VRNET) versus standardized patient in teaching neurological examinations for the medical students: a randomized, single-blind study

Autor: Tae Young Kong, Sang Gil Han, Junho Cho, Young Dae Kim

Publikováno v: BMC Medical Education
BMC Medical Education, Vol 21, Iss 1, Pp 1-8 (2021)

Background The conventional methods for teaching neurological examination with real patients to medical students have some limitations if the patient with the symptom or disease is not available. Therefore, we developed a Virtual Reality-based Neurol

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::26318989ad33f04ecfe8fc633c2e894a
http://europepmc.org/articles/PMC8444400

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Differential Biases and Variabilities of Deep Learning–Based Artificial Intelligence and Human Experts in Clinical Diagnosis: Retrospective Cohort and Survey Study (Preprint)

Autor: Dongchul Cha, Chongwon Pae, Se A Lee, Gina Na, Young Kyun Hur, Ho Young Lee, A Ra Cho, Young Joon Cho, Sang Gil Han, Sung Huhn Kim, Jae Young Choi, Hae-Jeong Park

BACKGROUND Deep learning (DL)–based artificial intelligence may have different diagnostic characteristics than human experts in medical diagnosis. As a data-driven knowledge system, heterogeneous population incidence in the clinical world is consid

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::64ff04edfff08bfe022a1dbb365a3a48
https://doi.org/10.2196/preprints.33049

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Deep Learning-Based Assistive Technology in Chest Radiograph Interpretation by Emergency Department Physicians: Prospective Study (Preprint)

Autor: Ji Hoon Kim, Sang Gil Han, Ara Cho, Hye Jung Shin, Song-Ee Baek

BACKGROUND Interpretation of chest radiographs (CRs) performed by emergency department (ED) physicians is inferior to that by radiologists. Recent studies have investigated the impact of deep learning-based assistive technology on CR interpretation (

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::9569ed5b3b620eeb1c45aba0a012743b
https://doi.org/10.2196/preprints.29612

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Differential Biases and Variabilities of Deep Learning–Based Artificial Intelligence and Human Experts in Clinical Diagnosis: Retrospective Cohort and Survey Study

Autor: Hae-Jeong Park, A Ra Cho, Ho Young Lee, Gina Na, Young Joon Cho, Sang Gil Han, Chongwon Pae, Young Kyun Hur, Jae Young Choi, Se A Lee, Sung Huhn Kim, Dongchul Cha

Publikováno v: JMIR Medical Informatics

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e2e6b81ae389e13525c1b00e10f6eb66
https://doi.org/10.2196/33049

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