International Journal

*corresponding author(s)

2025

  1. “Recovered graphene-hydrogel nanocomposites for multi-modal human motion recognition via optimized triboelectrification and machine learning“
    Thien Trung Luu, Hai Anh Thi Le, Yoonsang Ra, Teklebrahan Gebrekrstos Weldemhret, Hwiyoung Kim*, Kyungwho Choi, Dongwhi Choi, Dukhyun Choi, Yong Tae Park, Composites Part B: Engineering(2025, IF=12.7, in press)

2024

  1. “Predicting Post-Neoadjuvant Chemoradiotherapy PD-L1 expression with Multivariate Radiomics in Esophageal Squamous Cell Carcinoma“
    Hyun Do Jung, Tae Hoon Lee, Byoung Hyuck Kim, Hye Seung Lee, Jaeman Son, Hwiyoung Kim*, Hak Jae Kim, BMC Medical Imaging(2024, IF=2.90, under review)
  2. “Uncertainty Quantification in Automated Detection of Vertebral Metastasis Using Ensemble Monte Carlo Dropout ”
    Sooho Ahn, Seungjin Baek, Jiwoo Park, Jaewon Kim, Hyungjin Rhee, Yong Eun Chung, Hwiyoung Kim*, Young Han Lee*, Journal of Imaging Informatics in Medicine (2024, IF=4.20, in press)

2023

  1. “Identifying major predictors for parenting stress in a caregiver of autism spectrum disorder using machine learning models”
    Hangnyoung Choi, Jae Han Kim, Hwiyoung Kim*, Keun-Ah Cheon*, Frontiers in Neuroscience (2023, IF=5.15, in press)
  2. “Chest Radiography of Tuberculosis: Determination of Activity Using Deep Learning Algorithm”
    Ye Ra Choi, Soon Ho Yoon, Jihang Kim, Jin Young Yoo, Hwiyoung Kim, Kwang Nam Jin*, Tuberculosis and Respiratory Diseases (2023, IF=2.90)
  3. “Development of a deep learning based image processing tool for enhanced organoid analysis”
    Taeyun Park, Taeyul K. Kim, Yoon Dae Han, Kyung-A Kim, Hwiyoung Kim*, Han Sang Kim*, Scientific Reports (2023, IF=4.60, in press)
  4. “Detection of Pacemaker and Identification of MRI-conditional Pacemaker Based on Deep-learning Convolutional Neural Networks to Improve Patient Safety”
    Yoonah Do, Soo Ho Ahn, Sungjun Kim, Jin Kyem Kim, Byoung Wook Choi, Hwiyoung Kim*, Young Han Lee*, Journal of Medical Systems (2023, IF=5.30)
  5. “A machine learning model for predicting hepatocellular carcinoma risk in patients with chronic hepatitis B”
    Hye Won Lee, Hwiyoung Kim*, Taeyun Park, Soo Young Park, Young Eun Chon, Yeon Seok Seo, Jae Seung Lee, Jun Yong Park, Do Young Kim, Sang Hoon Ahn, Beom Kyung Kim, Seung Up Kim, Liver International (2023, IF=8.75)
  6. “Deep-learning-based detection of vertebral fracture and osteoporosis using lateral spine X-ray radiography“
    Namki Hong*, Sang Wouk Cho, Sungjae Shin, Seunghyun Lee, Seol A Jang, Seunghyun Roh, Young Han Lee, Yumie Rhee, Steven R Cummings, Hwiyoung Kim*, and Kyoung Min Kim*, Journal of Bone and Mineral Research (2023, IF=6.39)

2022

  1. “Performance of Deep Learning-based Pulmonary Nodule Detection with Synthetic Bone-suppressed Chest Radiographs“
    Hwiyoung Kim*, Kye Ho Lee*, Kyunghwa Han, Ji Won Lee, Jin Young Kim, Dong Jin Im, Yoo Jin Hong, Byoung Wook Choi, Jin Hur, JAMA Network Open (2022, IF=13.35)
  2. “Influence of computed tomography slice thickness on deep learning-based, automatic coronary artery calcium scoring software performance“
    Suh Young Kim, Young Joo Suh*, Hye-Jeong Lee, Hwiyoung Kim, Hyungi Seo, Hee Jun Park, Dong Hyun Yang ,Quantitative Imaging in Medicine and Surgery (2022, IF=4.63)
  3. “Clinical application of deep learning-based synthetic CT from real MRI to improve dose planning accuracy in Gamma Knife radiosurgery: a proof of concept study“
    So Hee Park, Dong Min Choi, In-ho Jung, Kyung Won Chang, Myung Ji Kim, Hyun Ho Jung, Jin Woo Chang, Hwiyoung Kim*, Won Seok Chang*, Biomedical Engineering Letters (2022, IF=3.92)
  4. “Development and Validation of a Visually Explainable Deep Learning Model for Classification of C-shaped Canals of the Mandibular Second Molars in Periapical and Panoramic Dental Radiographs“
    Yang Sujin, Hagyeong Lee, Byounghan Jang, Kee-Deog Kim, Jaeyeon Kim, Hwiyoung Kim*, Wonse Park,  Journal of Endodontics (2022, IF=4.17)

2021

  1. “A Deep Learning Model with High Standalone Performance for Diagnosis of Unruptured Intracranial Aneurysm“
    Bio Joo, Hyun Seok Choi*, Sung Soo Ahn, Jihoon Cha, So Yeon Won, Beomseok Sohn, Hwiyoung Kim, Kyunghwa Han, Hwa Pyung Kim, Jong Mun Choi, Sang Min Lee, Tae Gyu Kim, Seung-Koo Lee, Yonsei Medical Journal (2021, IF=3.05)
  2. “Radiomics machine learning study with small sample size: single random training-test set split may result in unreliable results”
    Chansik Ahn, Yae Won Park, Sung Soo Ahn, Kyounghwa Han, Hwiyoung Kim, Seung-Koo Lee, PLOS ONE (2021, IF=3.24)
  3. “Bone Radiomics Score Derived From DXA Hip Images Enhances Hip Fracture Prediction in Older Women” 
    Namki Hong, Heajeong Park, Chang Oh Kim, Hyeon Chang Kim, Jin-Young Choi, Hwiyoung Kim, Yumie Rhee*, Journal of Bone and Mineral Research (2021, IF=5.85)
  4. “Radiomics With Ensemble Machine Learning Predicts Dopamine Agonist Response in Patients With Prolactinoma”
    Yae Won Park, Jihwan Eom, Sooyon Kim, Hwiyoung Kim, Sung Soo Ahn, Cheol Ryong Ku, Eui Hyun Kim*, Eun Jig Lee, Sun Ho Kim, Seung-Koo Lee, Journal of Clinical Endocrinology & Metabolism (2021, IF=5.61)
  5. “Development of a deep learning-based algorithm for the automatic detection and quantification of aortic valve calcium”
    Suyon Chang, Hwiyoung Kim, Young Joo Suh, Dong Min Choi, Hyunghu Kim, Dong Kyu Kim, Jin Young Kim, Jin Young Yoo, Byoung Wook Choi, European Journal of Radiology (2021, IF = 4.53)
  6. “Using deep learning to predict temporomandibular joint disc perforation based on magnetic resonance imaging”
    Jae-Young Kim, Dong Wook Kim, Kug-Jin Jeon, Hwiyoung Kim, Jong-Ki Huh*, Scientific Reports (2021, IF=4.01)
  7. “Differentiation of recurrent glioblastoma from radiation necrosis using diffusion radiomics with machine learning model development and external validation”
    Yae Won Park, Dongmin Choi, Sung Soo Ahn*, Ji Eun Park, Hwiyoung Kim; Jong Hee Chang, Se Hoon Kim, Ho Sung Kim, Seung-Koo Lee, Scientific Reports (2021, IF=4.01)

2020

  1. “Development and Validation of a Deep Learning–Based Model to Distinguish Glioblastoma from Solitary Brain Metastasis Using Conventional MR Images“
    Ilah Shin*, Hwiyoung Kim, Chansik An, Sung Soo Ahn*, Kyunghwa Han, Sang Wook Kim, Ji Eun Park, Ho Sung Kim, Seung-Koo Lee, American Journal of Neuroradiology (2020, IF=3.38)
  2. “MRI Features May Predict Molecular Features of Glioblastoma in Isocitrate Dehydrogenase Wild-Type Lower-Grade Gliomas”
    Chaejung Park, Kyunghwa Han, Hwiyoung Kim, Sung Soo Ahn*, Yoon Seung Choi, Yae Won Park, Jong Hee Chang, Se Hoon Kim, Rajan Jain, Seung-Koo Lee, American Journal of Neuroradiology (2020, IF=3.38)
  3. “Radiomics features of hippocampal regions in magnetic resonance imaging can differentiate medial temporal lobe epilepsy patients from healthy controls”
    Yae Won Park, Yun Seo Choi, Song E Kim, Dongmin Choi, Kyunghwa Han, Hwiyoung Kim, Sung Soo Ahn, Sol-Ah Kim, Hyeon Jin Kim, Soo Mee Lim, Hyang Woon Lee*, Scientific Reports (2020, IF=4.01)
  4. “Radiomics risk score may be a potential imaging biomarker for predicting survival in isocitrate dehydrogenase wild-type lower-grade gliomas”
    Chaejung Park, Kyunghwa Han, Hwiyoung Kim, Sung Soo Ahn*, Yoon Seung Choi, Yae Won Park, Jong Hee Chang, Se Hoon Kim, Rajan Jain, Seung-Koo Lee, European Radiology 30:6464–6474 (2020, IF=4.10)
  5. “Diffusion tensor and postcontrast T1-weighted imaging radiomics to differentiate the epidermal growth factor receptor mutation status of brain metastases from non-small cell lung cancer“
    Yae Won Park, Chansik An, Kyunghwa Han, Dongmin Choi; Sung Soo Ahn*, Hwiyoung Kim, Sung Jun Ahn, Jong Hee Chang, Se Hoon Kim, Seung-Koo Lee, Neuroradiology (2020, IF=2.37)
  6. “Deep Learning for Automated Detection of Cyst and Tumors of the Jaw in Panoramic Radiographs”
    Hyunwoo Yang, Eun Jo, Hyung Jun Kim, In-ho Cha, Young-Soo Jung, Woong Nam, Jun-Young Kim, Jin-Kyu Kim, Yoon Hyeon Kim, Tae Gyeong Oh, Sang-Sun Han, Hwiyoung Kim* , Dongwook Kim*, Journal of Clinical Medicine (2020, IF=5.58)
  7. “Robust performance of deep learning for distinguishing glioblastoma from single brain metastasis using radiomic features: model development and validation“
    Sohi Bae, Chansik An, Sung Soo Ahn*, Hwiyoung Kim*, Kyunghwa Han, Sang Wook Kim, Ji Eun Park, Ho Sung Kim, Seung-Koo Lee, Scientific Reports (2020, IF=4.01)
  8. “Machine Learning Based Radiomic HPV Phenotyping of Oropharyngeal SCC: A Feasibility Study Using MRI”
    Beomseok Sohn, Yoon Seong Choi, Sung Soo Ahn, Hwiyoung Kim, Kyunghwa Han, Seung-Koo Lee, Jinna Kim*, Laryngoscope (2020, IF=2.34)

2019

  1. “Development of a deep neural network for generating synthetic dual-energy chest x-ray images with single x-ray exposure”
    Donghoon Lee, Hwiyoung Kim, Byoung Wook Choi*, Hee-Joung Kim*, Physics in Medicine and Biology (2019, IF=3.03)

2018

  1. “Machine learning to predict the occurrence of bisphosphonate-related osteonecrosis of the jaw associated with dental extraction: A preliminary report”
    Dong Wook Kim, Hwiyoung Kim, Woong Nam, Hyung Jun Kim, In-Ho Cha*, Bone 116 (2018, IF=4.36)

2017

  1. “Smartphone application for mechanical quality assurance of medical linear accelerators”,
    Hwiyoung Kim, Hyunseok Lee, Jong In Park, Chang Heon Choi, So-Yeon Park, Hee Jung Kim, Young Suk Kim, Sung-Joon Ye, Physics in Medicine and Biology 62:11, N254-270 (2017, IF=2.74)

2013

  1. “Development of real-time motion verification system using in-room optical images for respiratory-gated radiotherapy,”
    Yang-Kyun Park, Tae-geun Son, Hwiyoung Kim, Jaegi Lee, Wonmo Sung, Il Han Kim, Kunwoo Lee, Young-bong Bang,* Sung-Joon Ye, Journal of Applied Clinical Medical Physics 14:5, 25–42 (2013, IF=1.68)

2011

  1. “Qusai-breath-hold technique using personalized audio-visual biofeedback for respiratory motion management in radiotherapy,”
    Yang-Kyun Park, Siyoung Kim,Hwiyoung Kim, Il Han Kim, Kunwoo Lee, Sung-Joon Ye, Medical Physics 38:6, 3114–24 (2011, IF=3.32)
  2. “Development of an optical-based image guidance system: Technique detecting external markers behind a full facemask,”
    Hwiyoung Kim, Yang-kyun Park, Il Han Kim, Kunwoo Lee, Sung-Joon Ye, Medical Physics 38:6, 3006–12 (2011, IF=3.32)
  3. “MOSFET Dosimetry for Evaluation of Gonad Shielding during Radiotherapy,”
    Hwiyoung Kim, Yunseok Choi, So-Yeon Park, Yang-Kyun Park, Sung-Joon Ye, Journal of Radiation Protection 36:1, 23–27 (2011)