유재용, 박사
Jae Yong Yu, Doctor’s Course

e : icalust@gmail.com

Education

2018 – 2023  
Ph.D. in Digital Health, Sungkyunkwan University (SKKU),
Samsung Advanced Institute for Health Sciences & Technology (SAIHST)

2015 – 2017  
M.S. in Statistics, University of Seoul (UOS), KOREA

2008 – 2014  
B.S. in Statistics, ChungBuk National University (CBNU), ChungBuk, KOREA


Career

2017 – Present  
Statistics Researcher, Samsung Medical Center (SMC), Smart Health Lab (SHL)

2021.09 – 2022.09 (Global Research Training Program)
Visiting Research Fellow in Digital Smart & Health Office (DSHO), Tan Tock Seng Hospital (TTSH), Singapore
Visiting Research Fellow in Digital Medicine Lab, Duke-NUS, Singapore

2014 – 2015  
Statistics Researcher, Seoul National University of Hospital (SNUH), LEMS (Laboratory of Emergency Medical Services)


Skill Set

Data Science
– Programming (R,SAS)
– Machine Learning
– Medical Statistics
– Digital Healthcare
– Process Mining

Data Standard

– Common Data Model (CDM)


publication (orderded by date)

  • Yu, J.Y., Xie, F., Nan, L. et al. An external validation study of the Score for Emergency Risk Prediction (SERP), an interpretable machine learning-based triage score for the emergency department. Sci Rep 12, 17466 (2022). https://doi.org/10.1038/s41598-022-22233-w.
  • MinHa Kim, Jae Yong Yu, Hansol Chang, Sejin Heo, Se Uk Lee, Sung Yeon Hwang, Hee Yoon,Won Chul Cha, Tae Gun Shin, Taerim Kim. National Surveillance of Pediactric Out-of-Hospital Cardiac Arrest in Korea: The 10-Year Trend From 2009 to 2018 . Journal of Korea Medical Science. 2022;37(44),
  • Park H, Chae MK, Jeong W, Yu J, Jung W, Chang H, Cha WC. Appropriateness of Alerts and Physicians’ Responses With a Medication-Related Clinical Decision Support System: Retrospective Observational Study JMIR Medical Informatics. 18/09/2022:40511
  • Jonathan Shen You Ng, Reuben Jia Shun Ho, Jae Yong Yu, Yih Yng NG. Factors influencing success and safety of AED retrieval in out of hospital cardiac arrests in Singapore. Korean J Emerg Med Ser. 2022;26(2):97-111. Published online August 31, 2022 DOI: https://doi.org/10.14408/KJEMS.2022.26.2.097
  • Shim S, Yu JY (Co 1st Author),, Jekal S, Song YJ, Moon KT, Lee JH, Yeom KM, Park SH, Cho IS, Song MR, Cha WC, Hong JH. Development and Validation of Interpretable Machine Learning Models for Inpatient Fall Events and EMR Integration. Clin Exp Emerg Med. 2022 Sep 21. doi: 10.15441/ceem.22.354. PMID: 36128798.
  • Hansol Change, Jae Yong Yu (Co 1st Author), SunYoung Yoon and Cha WC. Machine learning-based suggestion for critical interventions in the management of potentially severe conditioned patients in emergency department triage . Sci Rep 12, 10537 (2022 June). https://doi.org/10.1038/s41598-022-14422-4
  • Yu JY, Chang HS, Cha WC. Predicting Mid-Term Survival of Patients During Emergency Department Triage for Resuscitation Decision. Journal of Anesthesia, Intensive Care, Emergency and Pain Medicine. 2022 Mar ;10.22514/sv.2022.018
  • Yu JY, Hong SJ, Shin SY. Stakeholders’ Requirements of Artificial Intelligence for Healthcare in Korea. Healthc Inform Res. 2022 Apr. 28(2):143-151 ; 10.4258/hir.2022.28.2.143
  • Dohyung Kim, Weong Jeong, Yu JY and WonChul Cha. Effect of fever or respiratory symptoms on leaving without being seen during the COVID-19 pandemic in South Korea. Clin Exp Emerg Med. 2022 Mar. 9(1):1-9 ;
  • Chang Hansol, JaeYong Yu (Co 1st Author) and Taerim Kim, “Change in ED process during the COVID-19 pandemic and its effect on that in presumed CVD patients”, Journal of Clinical Medicine, 2020. Nov
  • WonChul Cha, Won Jeong, JaeYong Yu and Jinwook choi, “Temporal Change in Alert Override Rate with a Minimally Interruptive Clinical Decision Support on a Next-Generation Electronic Medical Record”, Medicina, 2020. Nov
  • Yu JY, Jeong GY, Jeong OS, Chang DK, Cha WC. Machine Learning and Initial Nursing Assessment-Based Triage System for Emergency Department. Healthc Inform Res. 2020 Jan;26(1):13-19.
  • Yu JY, Park,C. “Comparison Study of Graphical Models for Text Mining”,
    Thesis (2017)


Symposium Presentation

  • Development and External Validation of Korean SERP (Score for Emergency Risk Prediction) using CDM (Common Data Model) for 3 hospitals in Korea (2022)

    Main Author / The Korea Society of Emergency Medical Informatics

  • External validation of the Score for Emergency Risk Prediction (SERP) an Interpretable Machine Learning-based Triage Score for the Emergency Department

    Main Author / Pre-hospital & Emergency Research Center, Singapore (2022)
    Development and Asian-wide validation of the Score for Interpretable Field Triage (SIFT) for predicting mortality in pre-hospital patients using the Pan-Asian Trauma Outcomes Study (PATOS) (2022)
    Main Author / Health Informatics Research

  • Suggesting Critical Interventions for the Management of Patients in the Emergency Department With Potentially Severe Conditions (2021)
    Main Author / Korea Society of Emergency Medicine

  • Development and Visualization of a Multiclass Prediction Model for Preliminary Diagnosis at the Emergency Department Using Machine Learning / KOSMI 2020 (Poster)

  • Difference of Emergency Department Frequent Users’ Clinical Characteristics between Two Tertiary Teaching Hospitals in South Korea(2019)
    Main Author / OHDSI Annual Symposium (Poster)

  • Pattern Recognition of Clinical Outcome Using Hospital Encounter Data(2018)
    Main Author / AMIA Annual Symposium (Poster)
  • Machine Learning based Triage System in Emergency Department(2018)
    Main Author / AMIA Annual Symposium (Poster)
  • Experience of Common data model in NEDIS system ( National Emergency Department information System) (2018)
  • Machine Learning based Triage System in Emergency Department(2018)
    Main Author / KSEM(Oral)


Award

• Best Oral Presentation Award (SAIHSTer GREEN) ,2022, Samsung Advanced Institute for Health Sciences and Technology

• Best Oral Presentation Award,2021, Korea Society of Emergency Medicine

• SAIHST Best scientific paper, 2021, Samsung Advanced Institute for Health Sciences and Technology

• Oral Presentation Award, 2018, Samsung Advanced Institute for Health Sciences and Technology

• Digital Health Hackathon award, 2018, Samsung Medical Center