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Jeong-Hyun Yoon

Yonsei University · Medicine

About the Lab

Professor Jeong-Hyun Yoon's research lab specializes in medical imaging and diagnostic radiology, with a focus on improving the accuracy and efficiency of thyroid and breast cancer detection. The lab investigates advanced ultrasound and elastography techniques, artificial intelligence applications in mammography and breast ultrasound, and the integration of computer-aided diagnosis systems to enhance diagnostic performance across varying levels of radiologist expertise. Research also emphasizes risk stratification tools such as TI-RADS and ATA guidelines, aiming to refine preoperative evaluation and reduce diagnostic uncertainty in large thyroid nodules. The lab is at the forefront of applying deep learning and AI algorithms to medical imaging to improve early detection, reduce interpretation time, and support precision patient management.

artificial intelligencebreast cancerultrasound elastographycomputer-aided diagnosisthyroid nodules

Research Overview

Papers
378
Total Citations
9,597
Papers (5y)
54
Primary Field
Medicine

Research Output Trend

Figures are computed from collected data and may differ slightly.

Publications per year (5y)
54total
2022
2023
2024
2025
2026
Citations per year (5y)
1,066total
20222023202420252026

Selected Papers

15
1
Article|229 citations·2015
Malignancy Risk Stratification of Thyroid Nodules: Comparison between the Thyroid Imaging Reporting and Data System and the 2014 American Thyroid Association Management Guidelines
Jung Hyun Yoon, Hye Sun Lee, Eun‐Kyung Kim, Hee Jung Moon, Jin Young Kwak
SJR Q1RadiologyOA

Both TIRADS and the ATA guidelines provide effective malignancy risk stratification for thyroid nodules. Nodules that do not meet the criteria for a specific pattern with the ATA guidelines have a relatively high risk of malignancy (18.2%).

Endocrinology, Diabetes and MetabolismMedicine
2
Review|160 citations·2023
Standalone AI for Breast Cancer Detection at Screening Digital Mammography and Digital Breast Tomosynthesis: A Systematic Review and Meta-Analysis
Jung Hyun Yoon, Fredrik Strand, Pascal Baltzer, Emily F. Conant, Fiona J. Gilbert, Constance D. Lehman, Elizabeth A. Morris, Lisa A. Mullen, Robert M. Nishikawa, Nisha Sharma, Ilse Vejborg, Linda Moy
SJR Q1RadiologyOA

Background There is considerable interest in the potential use of artificial intelligence (AI) systems in mammographic screening. However, it is essential to critically evaluate the performance of AI before it can become a modality used for independent mammographic interpretation. Purpose To evaluate the reported standalone performances of AI for interpretation of digital mammography and digital breast tomosynthesis (DBT). Materials and Methods A systematic search was conducted in PubMed, Google

Artificial IntelligenceComputer Science
3
Article|153 citations·2011
Interobserver Variability of Ultrasound Elastography: How It Affects the Diagnosis of Breast Lesions
Jung Hyun Yoon, Myung Hyun Kim, Eun‐Kyung Kim, Hee Jung Moon, Jin Young Kwak, Min Jung Kim
SJR Q1American Journal of Roentgenology

Elastography improves the specificity, positive predictive value, and accuracy of ultrasound. However, significant interobserver variability exists, with real-time elastographic performance showing fair agreement.

Radiology, Nuclear Medicine and ImagingMedicine
4
Article|113 citations·2011
The Diagnostic Accuracy of Ultrasound-Guided Fine-Needle Aspiration Biopsy and the Sonographic Differences Between Benign and Malignant Thyroid Nodules 3 cm or Larger
Jung Hyun Yoon, Jin Young Kwak, Hee Jung Moon, Min Jung Kim, Eun‐Kyung Kim
SJR Q1ThyroidOA

BACKGROUND: Although fine-needle aspiration biopsy (FNAB) is considered the standard for preoperative evaluation of thyroid nodules, the value of this has been questioned for large thyroid nodules. Here, we evaluated the diagnostic accuracy of ultrasound-guided FNAB (US-FNAB) for thyroid nodules that were 3 cm or larger as well as the sonographic differences between benign and malignant nodules in this size group. MATERIALS AND METHODS: There were 661 thyroid masses equal to or larger than 3 cm

Endocrinology, Diabetes and MetabolismMedicine
5
Article|111 citations·2013
Shear-wave elastography in the diagnosis of solid breast masses: what leads to false-negative or false-positive results?
Jung Hyun Yoon, Dae Chul Jung, Jong Tae Lee, Kyung Hee Ko
SJR Q1European RadiologyOA
Radiology, Nuclear Medicine and ImagingMedicine
6
Article|102 citations·2013
Diagnostic performances of shear wave elastography: which parameter to use in differential diagnosis of solid breast masses?
Eunjung Lee, Dae Chul Jung, Kyung Hee Ko, Jong Tae Lee, Jung Hyun Yoon
SJR Q1European RadiologyOA
Radiology, Nuclear Medicine and ImagingMedicine
7
Article|83 citations·2010
How to Approach Thyroid Nodules with Indeterminate Cytology
Jung Hyun Yoon, Jin Young Kwak, Eun‐Kyung Kim, Hee Jung Moon, Min Jung Kim, Ji Youn Kim, Hye Ryoung Koo, Myung Hyun Kim
SJR Q1Annals of Surgical OncologyOA
Endocrinology, Diabetes and MetabolismMedicine
8
Review|83 citations·2021
Deep Learning-Based Artificial Intelligence for Mammography
Jung Hyun Yoon, Eun‐Kyung Kim
SJR Q1Korean Journal of RadiologyOA

During the past decade, researchers have investigated the use of computer-aided mammography interpretation. With the application of deep learning technology, artificial intelligence (AI)-based algorithms for mammography have shown promising results in the quantitative assessment of parenchymal density, detection and diagnosis of breast cancer, and prediction of breast cancer risk, enabling more precise patient management. AI-based algorithms may also enhance the efficiency of the interpretation

Artificial IntelligenceComputer Science
9
Article|78 citations·2017
Application of Computer‐Aided Diagnosis on Breast Ultrasonography: Evaluation of Diagnostic Performances and Agreement of Radiologists According to Different Levels of Experience
Eun Cho, Eun‐Kyung Kim, Mi Kyung Song, Jung Hyun Yoon
SJR Q2Journal of Ultrasound in MedicineOA

OBJECTIVES: To investigate the feasibility of a computer-aided diagnosis (CAD) system (S-Detect; Samsung Medison, Co, Ltd, Seoul, Korea) for breast ultrasonography (US), according to radiologists with various degrees of experience in breast imaging. METHODS: From December 2015 to March 2016, 119 breast masses in 116 women were included. Ultrasonographic images of the breast masses were retrospectively reviewed and analyzed by 2 radiologists specializing in breast imaging (7 and 1 years of experi

Pathology and Forensic MedicineMedicine
10
Article|75 citations·2016
Diagnosis and Management of Small Thyroid Nodules: A Comparative Study with Six Guidelines for Thyroid Nodules
Jung Hyun Yoon, Kyunghwa Han, Eun‐Kyung Kim, Hee Jung Moon, Jin Young Kwak
SJR Q1RadiologyOA

Purpose To investigate the diagnostic performances of six guidelines used to assess thyroid nodules and to determine whether any of these guidelines identify cancers of aggressive form in this population. Materials and Methods From March 2007 to February 2010, 4696 thyroid nodules that were 1-2 cm in 4585 patients were diagnosed as benign or malignant on the basis of cytopathologic results. Ultrasonographic examinations of the thyroid nodules were retrospectively reviewed and categorized accordi

Endocrinology, Diabetes and MetabolismMedicine
11
Article|72 citations·2018
Tissue changes over time after polydioxanone thread insertion: An animal study with pigs
Jung Hyun Yoon, Sang Seop Kim, Seung Min Oh, Bong Cheol Kim, Wonsug Jung
SJR Q2Journal of Cosmetic Dermatology

BACKGROUND: Polydioxanone (PDO) sutures have been widely used to tighten and lift the face. However, why the complexion brightens and skin elasticity is maintained with a smaller facial outline after a PDO monofilament thread treatment remains unclear. AIMS: We aimed to determine what significant changes occur in the tissue over time when a PDO suture is inserted. METHODS: We selected four White Yucatan variety pygmy pigs with skin that most closely resembles the structure of human skin. 4-0 PDO

DermatologyMedicine
12
Article|70 citations·2015
Evaluation of Malignancy Risk Stratification of Microcalcifications Detected on Mammography: A Study Based on the 5th Edition of BI-RADS
Soo‐Yeon Kim, Ha Yan Kim, Eun‐Kyung Kim, Min Jung Kim, Hee Jung Moon, Jung Hyun Yoon
SJR Q1Annals of Surgical OncologyOA
Pathology and Forensic MedicineMedicine
13
Review|69 citations·2015
Effectiveness and Limitations of Core Needle Biopsy in the Diagnosis of Thyroid Nodules: Review of Current Literature
Jung Hyun Yoon, Eun‐Kyung Kim, Jin Young Kwak, Hee Jung Moon
SJR Q2Journal of Pathology and Translational MedicineOA

Fine needle aspiration (FNA) is currently accepted as an easy, safe, and reliable tool for the diagnosis of thyroid nodules. Nonetheless, a proportion of FNA samples are categorized into non-diagnostic or indeterminate cytology, which frustrates both the clinician and patient. To overcome this limitation of FNA, core needle biopsy (CNB) of the thyroid has been proposed as an additional diagnostic method for more accurate and decisive diagnosis for thyroid nodules of concern. In this review, we f

Endocrinology, Diabetes and MetabolismMedicine
14
Article|66 citations·2008
Sonographic Features of the Follicular Variant of Papillary Thyroid Carcinoma
Jung Hyun Yoon, Eun‐Kyung Kim, Soon Won Hong, Jin Young Kwak, Min Jung Kim
SJR Q2Journal of Ultrasound in Medicine

OBJECTIVE: The purpose of this study was to evaluate the sonographic findings of the follicular variant of papillary thyroid carcinoma (FVPTC) and to assess the role of preoperative fine-needle aspiration biopsy (FNAB). METHODS: The sonographic findings of 27 thyroid nodules in 26 patients (2 male and 24 female; mean age, 45 years) with surgically proven FVPTC were reviewed retrospectively. Findings were categorized according to the echogenicity, margin, shape, and presence of microcalcification

Endocrinology, Diabetes and MetabolismMedicine
15
Article|62 citations·2011
Inadequate Cytology in Thyroid Nodules: Should We Repeat Aspiration or Follow-Up?
Jung Hyun Yoon, Hee Jung Moon, Eun‐Kyung Kim, Jin Young Kwak
SJR Q1Annals of Surgical OncologyOA
Endocrinology, Diabetes and MetabolismMedicine

Research Areas

Endocrinology, Diabetes and MetabolismRadiology, Nuclear Medicine and ImagingPathology and Forensic MedicineCancer ResearchArtificial IntelligenceOncology

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