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Beyond Data: Actionable AI — Review of the 2023 Fall Conference of the Korean Society of Medical Informatics

Lee Y, Ko T, Yang K, on behalf of the KOSMI’s Academic Committee

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The first use of hypothermic machine perfusion in Korea to recover a procured kidney graft and prevent prolonged cold ischemic time: a case report

Shin YH, Ko T, Park JH, Chang WB

To overcome the shortage of donor grafts in kidney transplantation (KT), the use of marginal grafts has evolved. However, prolonged cold ischemic time (CIT) is especially critical when using marginal...
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Review of the 2024 Spring Conference of the Korean Society of Medical Informatics – Omnibus Omnia

Lee J, Lee S, Baik SY, Ko T, Yang K, Lee Y, KOSMI’s Academic Committee

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Review of the Spring Conference of the Korean Society of Medical Informatics 2023: Revolution and Innovation in Smart Healthcare

Park J, Ko T, Lee Y, Yang K

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Degree of Satisfaction with Indirect Medical Oversight Programs to 119 Rescue Services

Lee CJ, Je DW, Ko T, Choe MS

  • KMID: 2333720
  • J Korean Soc Emerg Med.
  • 2014 Feb;25(1):51-59.
PURPOSE: The purpose of this study was to identify the degree of satisfaction with indirect medical oversight programs and its determinants. METHODS: Gumi 119 rescuers participated in indirect medical oversight programs,...
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Machine Learning-Based Prediction of Korean Triage and Acuity Scale Level in Emergency Department Patients

Choi SW, Ko T, Hong KJ, Kim KH

OBJECTIVES: Triage is a process to accurately assess and classify symptoms to identify and provide rapid treatment to patients. The Korean Triage and Acuity Scale (KTAS) is used as a...
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Effectiveness of Indirect Medical Oversight on the Quality of Prehospital Emergency Care by Emergency Medical Technicians

Lee JT, Park SH, Lee CH, Kim YK, Lee CJ, Je DW, Ko T, Choe MS, Kim OJ

  • KMID: 2333565
  • J Korean Soc Emerg Med.
  • 2013 Dec;24(6):684-693.
PURPOSE: This study examined the effect of indirect medical oversight on the quality of prehospital emergency care by emergency medical technicians. METHODS: Indirect medical oversight was applied for a year and...
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Prediction of Cardiovascular Complication in Patients with Newly Diagnosed Type 2 Diabetes Using an XGBoost/GRU-ODE-Bayes-Based Machine-Learning Algorithm

Lee J, Choi Y, Ko T, Lee K, Shin J, Kim HS

Background: Cardiovascular disease is life-threatening yet preventable for patients with type 2 diabetes mellitus (T2DM). Because each patient with T2DM has a different risk of developing cardiovascular complications, the accurate...
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Analysis of the Impact on Community Health after Accidental Leak of Hydrofluoric Acid

Kim YG, Lee JT, Park SH, Lee CH, Choe MS, Je DW, Lee CJ, Ko T, Jo HJ

  • KMID: 2203672
  • J Korean Soc Clin Toxicol.
  • 2013 Dec;11(2):106-113.
PURPOSE: The purpose of this study is to verify the influence of a massive hydrofluoric acid spill on community health through patients who claimed to have been exposed. METHODS: We analyzed...
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