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Deep learning model for decision of revascularization method for multi-vessel conronary artery disease 

Byeolhee Kim, Junhee Kim, Younghak Kim, Taejoon Jun, Jungmin Ahn

2023 Korea Software Congress(KSC)

In-hospital Mortality Prediction of Heart Failure Patients using unstructured medical text data

Seohyun Park, Taejoon Jun, Younghak Kim

2023 Korea Software Congress(KSC)

Predicting  Disease  Progression  from  Idiopathic  Cytopenia  of Undetermined  Significance  to  Myeloid  Malignancies  using  aMachine  Learning-Based  Approach

Jiye Han, Eunji Choi,  Taejoon Jun,  Han-Seung Park, Yunsuk Choi, Jung-Hee Lee, Kyoo-Hyung Lee, Young-Hak Kim, Je-Hwan  Lee

2023 Korea Software Congress(KSC)

Predicting Disease Progression from Idiopathic Cytopenia of Undetermined Significance to Myeloid Malignancies Using a Machine Learning-Based Approach

Eun-Ji Choi MDPhD, Jiye Han, Tae Joon Jun PhD, Han-Seung Park MD, Yunsuk Choi MDPhD, Jung-Hee Lee MD PhD, Kyoo Hyung Lee MD PhD, Young-Hak Kim MD PhD, Je-Hwan Lee MDPhD

Blood: Emerging Tools, Techniques and Artificial Intelligence in Hematology

Abstract 13223: Assessing Cardiomediastinal Abnormalities Through Quantitative Evaluation of Chest X-rays: A Multicenter Validation in Various Clinical Cohorts

June-Goo Lee, Tae Joon Jun, Cherry Kim, Young Joo Suh, Marly Van Assen, Carlo N De, Iksung Cho, Young-Hak Kim and Dong Hyun Yang

Circulation: Epidemiology, Big Data and Precision Medicine

(Session Title: Large Language Models(IE. ChatGPT) and AI Changing the way we asses risks and identify patients)


A deep-learning based model for identification of prognostic factors and prediction of graft survival in kidney transplant patients

Jin-Myung Kim, Sung Shin, Young Hoon Kim, Hyunwook Kwon, Youngmin Ko, Hye Eun Kwon, Jae Jun Lee, Sang-Hyun Hwang, Tae Joon Jun

Clinical Transplantation and Research(CTR)

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