[Paper list]
[Under Review]
1. JY Yu, Hansol Chang, Development and Validation of Asian-wide Time-Dependent Analysis of Out-of-Hospital Cardiac Arrest Outcomes Using Interpretable Machine Learning in a Multinational Cohort, 2025, Lancet Digital Health (under review)
2. JY Yu, CY Ko, YR Park, The Influence of News Media Exposure on Deliberate Self-harm and Suicide: Evidence from a Korean Nationwide Cohort Study, 2025, Jama Psychiatric (under review)
3. YJ Cho, JY Yu, YR Park, Game-based Shadow-induced Forgetting: Effects of Consciousness, Emotional Valence, and Temporal Dynamics on Memory Suppression, 2025, npj Digital Medicine (under review)
4. JW Park*, WS Sim*, JY Yu, Park YR*, Evaluation of context-aware prompting techniques for classification of tumor response categories in radiology reports using large language model, 2024, European Radiology (under review) (IF: 10.04)
5. Jae Yong Yu*, Minjung Kathy Chae*, Ju Hyung Ha, Woo Hyun Jung, Sung Yung Yoon, Won Chul Cha*. A time-adaptive machine-learning model to predict hemostatic intervention for suspected upper gastrointestinal bleeding patients in the emergency department. 2023, Mayo Clinic Proceedings (under review) (IF: 12.21)
6. Jae Yong Yu*, Han Sol Chang, Lin Xinyi, Feng Xie, Liu Nan, Sun Young Yoon, Marcus Eng Hock Ong, Yih Yng Ng, Michel Chia, Won Chul Cha*. Development and External Country Validation of Model Agnostic Interpretable Triage Score for Emergency Departments. 2023, JMIR Medical Informatics (under review) (IF: 7.94)
7. Hansol Chang; Jae Yong Yu; Hyunjung Park; Yee Jun Song; Sejin Heo; Jong Eun Park; Gun Tak Lee; Se Uk Lee; Hee Yoon; Sung Yeon Hwang; Won Chul Cha. Implementation and Post-implementation investigation of ‘Critical Interventions’ prediction model following development of artificial intelligence based Clinical Decision Support System. 2023 JMIR (under review) (IF: 7.03)
[Under Revision]
8. Jae Yong Yu* Soo Young Jang, Chan Young Ko, Yu Rang Park*, Development of screening tool for autism spectrum disorder using gross and fine motor development evaluation in toddler based on Interpretable machine learning, 2023, JMIR (under major revision) (IF: 7.03)
[Published]
1. Soo Young Jang*, Jae Yong Yu (co 1st author)*, Yu Rang Park*, 2025, Journal of Gastroenterology
2. DS Kim, JY Yu (co 1st author)*, SY Hwang, DW Jeong, Adjusting on-scene CPR duration based on transport time interval in out-of-hospital cardiac arrest: a nationwide multicenter study, 2025, scientific reports
3. SeJin Heo, Jae Yong Yu, SW LEE*, Federated learning for predicting critical intervention and poor clinical outcomes at emergency department triage stage, 2025, Signa Vitae
4.Jang BK*, Kim SW*, Yu JY, Park YR*, Classification models for osteoarthritis grades of multiple joints based on continual learning, 2025, IEEE Transactions on Medical Imaging (under review) (IF: 10.04)
5. Javi*, Jae Yong Yu, Won Chul Cha*, Computationally efficient and stable real-world synthetic emergency room electronic health record data generation: high similarity and privacy preserving diffusion model approach: A retrospective cohort study, 2024, JAMIA Medical Informatics (IF: 7.94)
6. Ju Hee Lee*, Jae Yong Yu* (Co 1st Author), Won Chul Cha*, Development and Validation of Interpretable Machine Learning Models for Inpatient Fall Events and EMR integration, 2024, KSNS
7. Jeon, Song, Yu, Cha, Prediction of Postdonation Renal Function using Machine Learning Techniques and Conventional Regression Models in Living Kidney Donors, 2024, JNEP
8. Tae Hyun Kim* Jae Yong Yu*(Co 1st Author), Yu Rang Park. PPFL : PPFL: A personalized progressive federated learning method for leveraging different healthcare institution-specific features, 2024, iScience (IF: 7.03)
9. Heo*, Kang*, Yu, Kim, Lee, Kim, Hwangbo, Park, Shin, Ryu, Kim, Jung, Chegal, Lee, Park. Development and Verification of a Time Series AI Model for Acute Kidney Injury Detection Based on a Multicenter Distributed Research Network. 2024, JMIR Medical Informatics ((IF: 3.2)
10. Jae Yong Yu*, Woo Seop Shim*, Yu Rang Park. Development of Quantum Support Vector Machine for predicting mortality of Early onset colorectal cancer, 2024, Applied Soft computing (IF: 8.7)
11. Jae Yong Yu*, Do Yeop Kim*, Sun Young Yoon, Gan Soo Han, Kyung Won Jeong, Rae Woong Park, Jun Myung Gwon, Feng Xie, Liu Nan, Marcus Eng Hock Ong, Yih Yng Ng, Hyung Jun Ju and Won Chul Cha. Inter-hospital Validation of Interpretable Machine Learning-based Triage Score for the Emergency Department using Common Data Model. 2024, Scientific Reports (IF: 4.9)
12. Won Jeong, JaeYong Yu, Won Chul cha, Effect of knowledgebase transition of a clinical decision support system on medication order and alert patterns in an emergency department, Scientific Reports, 2023 (IF: 4.997)
13. Hansol Chang*, Jae Yong Yu* (Co 1st Author), Geun Hyeong Lee, Sejin Heo, Se Uk Lee, Sung Yeon Hwang, Hee Yoon, Won Chul Cha, Tae Gun Shin, Min Seob Sim, Ik Joon Jo and Taerim Kim*. Clinical support system for triage based on federated learning and the Korea Triage and Acuity Scale. 2023, Heliyon (IF: 3.776)
14. Soon Chul Heo*, Jae Yong Yu* (Co 1st Author), Eun Ae Kang, Hyunah shin, Keyngmin Ryu, Chungsoo Kim, Rae Woong Park, Yul Hwangbo, Yu Rang Park*, Development and Verification of Time-Series Deep Learning for Drug-Induced Liver Injury Detection in Patients Taking Angiotensin II Receptor Blockers: A Multicenter Distributed Research Network Approach, 2023, Healthcare Informatic Research
15. Jeon*, Yu* (Co 1st Author), Song, Jung, Lee, Lee, Huh, Cha and Jang. Prediction tool for renal adaptation after living kidney donation using interpretable machine learning. 2023, Frontiers in Medicine (IF : 5.058)
16. DH Yoon, SJ Heo, JY Yu, SU Lee, WC Cha. Effect of artificial-intelligent chest radiographs reporting system in an emergency department. 2023, Signa Vitae (IF : 1.1)
17. Han sol chang, Weon Jung, JY Yu, WC Cha, Taerim Kim, EARLY PREDICTION OF UNEXPECTED LATENT SHOCK IN THE EMERGENCY DEPARTMENT USING VITAL SIGNS,2023, Shock (IF : 3.533)
18. Seunghyun Lee, Jae yong Yu, Yuri Kim, Myungjin Kim and Helen Lew. Application of an Interpretable Machine Learning for Estimating Severity of Graves’ Orbitopathy Based on Initial Finding. Journal of Clinical Medicine, 2023 (IF : 4.964)
19. Jae Yong Yu*, Sejin Heo*, Feng Xie, Nan Liu, Marcus Eng Hock Ong, Yih Yng Ng, Sang Do shin, Kentaro Kajino, Won Chul Cha. Development and Asian-wide validation of the Grade for Interpretable Field Triage (GIFT) for predicting mortality in pre-hospital patients using the Pan-Asian Trauma Outcomes Study (PATOS). The Lancet Regional Health - Western Pacific, 2023,100733, ISSN 2666-6065 (IF : 7.4)
20. 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. (IF : 4.6)
21.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), (IF : 4.5)
22. 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 (IF : 3.2)
23. 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
24. 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.
25. 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 (IF : 4.6)
26. 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 (IF :1.1)
27. 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
28. 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
29. 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 (IF : 4.6)
30. 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 (IF : 2.6)
31. 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.