Kyunghwa Han

RESEARCH INTERESTS

•      ROC curve analysis

•      Clinical validation of AI in radiology

•      Stability of radiomics features

PROFESSIONAL ACTIVITIES

•       Director of Research, Korean Society of Imaging Informatics in Medicine

•       Committee Member, Radiology Imaging Network of Korea for Clinical Research in Korean Society of Radiology

•       Member, Korean Society of Statistics; International Biometric Society; Korean Society of Health Informatics and Statistics; Radiological Society of North America

(Journal)

•       Statistical Consultant, Korean Journal of Radiology, 2016-present

•       Statistical Editor, Archives of Plastic Surgery, 2015-present

•       Statistical Reviewer, Journal of Health Informatics and Statistics, 2018-present

PROJECTS

• Study Design and Statistical Methods for Validating Prediction Model for Diagnosis or Prognosis and Stability of Radiomics Feature in Medical Imaging with Multi-Center and/or Multi-Reader Study, Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education(NRF-2021R1I1A1A01059893) [2021-2024]

• Study Design and Statistical Methods for Validating Clinical Effect of Deep Leaning based Computer-Aided Detection and Diagnosis System in Medical Imaging with Multi-Center and/or Multi-Reader Study, Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education(NRF-2018R1A6A3A01013583) [2018-2020]

LECTURES

• Fall 2023, Data Mining Applications in Big Data, Yonsei University Graduate School of Public Health (SPG6015-01)

• Spring 2023, Special Topics in Biostatistics, Department of Biostatistics and Computing, Yonsei University Graduate School (BSC6007-01): course on Statistical Evaluation of Medical Tests for Classification and Prediction

• Fall 2022, Data Mining Applications in Big Data, Yonsei University Graduate School of Public Health (SPG6015-01)

• Spring 2021, Special Topics in Biostatistics, Department of Biostatistics and Computing, Yonsei University Graduate School (BSC6007-01): course on Statistical Evaluation of Medical Tests for Classification and Prediction

• Fall 2020, Data Mining Applications in Big Data, Yonsei University Graduate School of Public Health (SPG6015-01)

• Fall 2020, Special Topics in Biostatistics, Department of Biostatistics and Computing, Yonsei University Graduate School (BSC6007-01): course on Statistical Evaluation of Medical Tests for Classification and Prediction

• Fall 2019, Data Mining Applications in Big Data, Yonsei University Graduate School of Public Health (SPG6015-01)

• Fall 2019, Special Topics in Biostatistics, Department of Biostatistics and Computing, Yonsei University Graduate School (BSC6007-01): course on Statistical Evaluation of Medical Tests for Classification and Prediction

• Spring 2018, Special Topics in Biostatistics, Department of Biostatistics and Computing, Yonsei University Graduate School (BSC6007-01): course on Statistical Evaluation of Medical Tests for Classification and Prediction

SELECTED PRESENTATIONS

• • Korean Society of Radiology, 2024 RINK-CR Seminar 

“Statistical Methods for Clinical Performance Assessment of Artificial Intelligence in Medical Imaging” (May 2024)

• Korean Statistical Society, 2023 winter conference

Kwon Y, Han K, Suh YJ, Jung I. “Comparative Analysis of LASSO and Group LASSO: Performance, Practicality, and Application” (Dec 2023) 

• • Korean Statistical Society, 2023 summer conference

Yuri So, Kwon Y, Han K, Jung I. “Comparison of variable selection through the combination of sub-sampling method and weighting method with imbalanced data” (Dec 2023) 

• • Korean Statistical Society, 2022 winter conference

Nahm S, Han K, Jung I. “Comparison of Different Approaches to Multi-reader Multi-case ROC Curve Analysis” (Dec 2022) 

• • Asian Oceanian Congress of radiology & Korean Congress of Radiology 2022

     Han K. “Statistical methods for AI validation: from conventional to recent trends" (Sep 2022)

• • Bayer Korea. RadioSTAR Webinar, 

“Advanced Time-to-Event Analysis”, “Statistical Methods in Multireader Study and Reader Reliability” (Jul 2022)

• Korean Statistical Society, 2022 summer conference

Ryu L, Kwon Y, Han K, Jung I. “Random survival forest-based weighted variable selection for survival data” (Jun 2022) 

• Korean Society of Radiology, 2022 Korean Spring Symposium of Radiology, 

“How to do: Statistical Considerations for Multicenter study” (Jun 2022)

• Asian Society of Cardiovascular Imaging, Advanced School for Core Investigators

 “Statistical Methods in Cardiovascular Imaging” (2015-2022)

• Seoul National University Bundang Hospital, Advanced Statistics Lecture

“Development and Validation of Clinical Prediction Model: TRIPOD Statement” (Apr 2022)

• Department of Biomedical System Informatics, Yonsei University College of Medicine, Seminar for Biomedical System Informatics

“Data Science in Radiology as a Statistician” (Apr 2022)

• Korean Statistical Society, 2021 fall conference

Han K, Kim S, Choi BW, Jung I. “A Statistical Method for Comparing ROC Curves of Multireaders with Standalone Artificial Intelligence” (Nov 2021)

• Korean Statistical Society, 2021 fall conference

Kwon Y, Han K, Jung I. “Stability selection for LASSO with weights based on AUC” (Nov 2021)

• Ministry of Food and Drug Safety (MFDS), Seminar on Standard for Evaluating Performance of Medical AI device

“Statistical Considerations for Labeling and Test Data Set” (May 2021)

• Asian Society of Magnetic Resonance in Medicine (ASMRM) & International Congress on Magnetic Resonance Imaging (ICMRI), 2020 Fall Congress

“Statistician's Suggestions: Common Statistical Errors in Radiology Papers” (Nov 2020)

• Radiology Society of North America,105th Scientific assembly and Annual meeting, 

Han K, Kim S, Choi BW, Jung I. A proper Statistical Method for Comparing Diagnostic Performances Between Stand-Alone Artificial Intelligence System and Multiple Readings from Multi-Reader Diagnostic Performance Study (Dec 2019)

• Korean Statistical Society, 2019 fall conference

Kim S, Han K, Jung I. “Firth’s logistic regression for separation problem: comparing between R-logistf and SAS-LOGISTIC” (Nov 2019)

• Korean Statistical Society, 2018 fall conference

Shin HS, Han K, Jung I. “Comparison of the performance of diagnostic accuracy measures for ordinal outcomes: A simulation study” (Nov 2018)

• International Workshop on Pulmonary Functional Imaging 2017

    “Clinical Prediction Model: Statistical Framework for Prediction Medicine” (Mar 2017)

• Korean Statistical Society, 2016 fall conference

Kim K, Han K, Jung I. “Estimation of the optimal cutoff in multireader study” (Nov 2016) 

• Korean Statistical Society, 2014 fall conference

Han K, Jung I. “A study on diagnostic accuracy when there are multi-category diagnostic groups in multiple measurements per subject” (Oct 2014)

SELECTED PUBLICATIONS [Google Scholar] 

(Research in Radiology, Validation in AI / Radiomics)

• Park J, Oh K, Han K* & Lee H*. Patient-centered radiology reports with generative artificial intelligence: adding value to radiology reporting. Scientific Reports 14.1 (2024): 13218.

• Suh YJ, Han K, Kwon Y, et al. Computed Tomography Radiomics for Preoperative Prediction of Spread Through Air Spaces in the Early Stage of Surgically Resected Lung Adenocarcinomas. Yonsei Med J. 2024 Mar;65(3):163-173.

• Park YW, Park JE, Ahn SS, Han K, et al. Deep learning-based metastasis detection in patients with lung cancer to enhance reproducibility and reduce workload in brain metastasis screening with MRI: a multi-center study. Cancer Imaging 24, 32 (2024). 

• Hong YJ, Han K, Lee HJ, Hur J, Kim YJ, Kim MJ & Choi BW. Assessment of Feasibility and Interscan Variability of Short-time Cardiac MRI for Cardiotoxicity Evaluation in Breast Cancer. Radiology: Cardiothoracic Imaging, 2024; 6(1), e220229. 

• Shin HJ, Han K, Ryu L and Kim EK. The impact of artificial intelligence on the reading times of radiologists for chest radiographs. npj Digit. Med. 6, 82 (2023). https://doi.org/10.1038/s41746-023-00829-4 

• Park YW1, Han K1, Kim S. et al. Revisiting prognostic factors in glioma with leptomeningeal metastases: a comprehensive analysis of clinical and molecular factors and treatment modalities. J Neurooncol 162, 59–68 (2023). 

• Chang S, Han K, Lee S, Yang YJ, Kim PK, Choi BW, Suh YJ. Automated Measurement of Native T1 and Extracellular Volume Fraction in Cardiac Magnetic Resonance Imaging Using a Commercially Available Deep Learning Algorithm. Korean J Radiol. 2022 Dec;23(12):1251-1259.

• Lee, JW, Park, CH, Im, DJ, Lee KH, Kim TH, Han K* and Hur J*. CT-based radiomics signature for differentiation between cardiac tumors and thrombi: a retrospective, multicenter study. Sci Rep 2022;12, 8173.

• Lee SE, Han K, Kim EK. Application of artificial intelligence-based computer-assisted diagnosis on synthetic mammograms from breast tomosynthesis: comparison with digital mammograms. Eur Radiol. 2021;31(9):6929-37.

• Kim K, Kim S, Han K, Bae H, Shin J, Lim JS. Diagnostic Performance of Deep Learning-Based Lesion Detection Algorithm in CT for Detecting Hepatic Metastasis from Colorectal Cancer. Korean J Radiol. 2021;22(6):912-21. 

• An C, Park YW, Ahn SS, Han K, Kim H, Lee S-K. Radiomics machine learning study with a small sample size: Single random training-test set split may lead to unreliable results. PLoS ONE  2021;6(8): e0256152. 

• Kim HE, Kim HH, Han BK, Kim KH, Han K, Nam H, et al. Changes in cancer detection and false-positive recall in mammography using artificial intelligence: a retrospective, multireader study. The Lancet Digital health. 2020;2(3):e138-e48.

• Park VY, Han K, Lee E. et al. Association Between Radiomics Signature and Disease-Free Survival in Conventional Papillary Thyroid Carcinoma. Sci Rep 2019;9, 4501.

(Methodology in Radiology)

• Park SH, Han K and Lee JG. Conceptual review of outcome metrics and measures used in clinical evaluation of artificial intelligence in radiology. Radiol med. 2024. 

• Han K*, Ryu L. Statistical Methods for the Analysis of Inter-Reader Agreement Among Three or More Readers. Korean J Radiol. 2024 Apr;25(4):325-327. 

• Park SH, Han K, Jang HY, Park JE, Lee JG, Kim DW, et al., Methods for clinical evaluation of artificial intelligence algorithms for medical diagnosis. Radiology, 2023;306(1):20-31.

• Ryu L, Han K.  Machine Learning vs. Statistical Model for Prediction Modelling: Application in Medical Imaging Research. J Korean Soc Radiol. 2022 Nov;83(6):1219-1228. 

• Park SH, Han K.   How to Clearly and Accurately Report Odds Ratio and Hazard Ratio in Diagnostic Research Studies? Korean J Radiol. 2022 Aug;23(8):777-784. 

• Han K, Jung I. Restricted Mean Survival Time for Survival Analysis: A Quick Guide for Clinical Researchers. Korean J Radiol. 2022 May;23(5):495-499. 

• Park SH, Han K, Park SY. Mistakes to Avoid for Accurate and Transparent Reporting of Survival Analysis in Imaging Research. Korean J Radiol. 2021;22(10):1587-93.

• Park SH, Han K. Methodologic Guide for Evaluating Clinical Performance and Effect of Artificial Intelligence Technology for Medical Diagnosis and Prediction. Radiology. 2018;286(3):800-9.

• Park JE1, Han K1, Sung YS, Chung MS, Koo HJ, Yoon HM, et al. Selection and Reporting of Statistical Methods to Assess Reliability of a Diagnostic Test: Conformity to Recommended Methods in a Peer-Reviewed Journal. Korean J Radiol. 2017;18(6):888-97.

• Han K, Song K, Choi BW. How to Develop, Validate, and Compare Clinical Prediction Models Involving Radiological Parameters: Study Design and Statistical Methods. Korean J Radiol. 2016;17(3):339-50.

(Statistical Methodology)

• Kwon Y, Han K, Suh YJ, and Jung I. Stability selection for LASSO with weights based on AUC. Scientific Reports, 2023, 13(1): 5207. 

• Han K and Jung I. Assessing Correlation between Two Variables in Repeated Measurements Using Mixed Effect Models. Korean Journal of Applied Statistics. 2015. 28(2):201–210.

(Systematic Review and Meta-analysis)

• Chang S, Han K, Suh YJ. et al. Quality of science and reporting for radiomics in cardiac magnetic resonance imaging studies: a systematic review. Eur Radiol 2022;32, 4361–4373.

• Kim JY, Han K, Suh YJ. Prevalence of abnormal cardiovascular magnetic resonance findings in recovered patients from COVID-19: a systematic review and meta-analysis. J Cardiovasc Magn Reson. 2021;23(1):100. 

• Kim JY, Suh YJ, Han K, Kim YJ, Choi BW. Diagnostic Value of Advanced Imaging Modalities for the Detection and Differentiation of Prosthetic Valve Obstruction: A Systematic Review and Meta-Analysis. JACC Cardiovascular imaging. 2019;12(11 Pt 1):2182-92.

• Park CH1, Han K1, Hur J, Lee SM, Lee JW, Hwang SH, et al. Comparative effectiveness and safety of pre-operative lung localization for pulmonary nodules: a systematic review and meta-analysis. Chest. 2016.

(SEER data)

• Yoon JK, Lee J, Kim EK, Yoon JH, Park VY, Han K* and Kwak JY*. Strap muscle invasion in differentiated thyroid cancer does not impact disease-specific survival: a population-based study.  Sci Rep. 2020;10(1):18248.

• Han K, Kim EK, Kwak JY. 1.5-2 cm tumor size was not associated with distant metastasis and mortality in small thyroid cancer: A population-based study. Sci Rep. 2017;7:46298.

EMPLOYMENT

•     Assistant Professor, Department of Radiology, Research Institute of Radiological Science, Yonsei University College of Medicine, 2024-present

•     Research Associate Professor, Research Institute of Radiological Science, Yonsei University College of Medicine, 2022-2023

•     Research Assistant Professor, Research Institute of Radiological Science, Yonsei University College of Medicine, 2016-2021

•     Postdoctoral Researcher, Yonsei Biomedical Research Institute, Yonsei University College of Medicine, 2015

•     Research Assistant, Biostatistics Collaboration Unit, Gangnam Medical Research Center, Yonsei University College of Medicine, 2012-2015

•     Research Assistant, Biostatistics Collaboration Unit, Department of Research Affairs, Yonsei University College of Medicine, 2008-2012

•     Research Assistant, Department of Biostatistics, Yonsei University College of Medicine, 2006-2008

EDUCATION

•      Ph.D, Biostatistics and Computing, Yonsei University, 2015

•      M.S., Biostatistics and Computing, Yonsei University, 2008

•      B.S., Statistics, Sookmyung Women’s University, 2006