Sunggyun Park

2.3k total citations · 2 hit papers
12 papers, 1.2k citations indexed

About

Sunggyun Park is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Computer Vision and Pattern Recognition. According to data from OpenAlex, Sunggyun Park has authored 12 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Radiology, Nuclear Medicine and Imaging, 5 papers in Pulmonary and Respiratory Medicine and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Sunggyun Park's work include COVID-19 diagnosis using AI (9 papers), Radiomics and Machine Learning in Medical Imaging (7 papers) and Lung Cancer Diagnosis and Treatment (5 papers). Sunggyun Park is often cited by papers focused on COVID-19 diagnosis using AI (9 papers), Radiomics and Machine Learning in Medical Imaging (7 papers) and Lung Cancer Diagnosis and Treatment (5 papers). Sunggyun Park collaborates with scholars based in South Korea, Ethiopia and United States. Sunggyun Park's co-authors include Chang Min Park, Eui Jin Hwang, Jin Mo Goo, Jong Hyuk Lee, Kwang-Nam Jin, Ju Gang Nam, Donggeun Yoo, In So Kweon, Joon‐Young Lee and Jae Ho Sohn and has published in prestigious journals such as Clinical Infectious Diseases, Radiology and Medicine.

In The Last Decade

Sunggyun Park

11 papers receiving 1.2k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Development and Validation of Deep Learning–based Automatic Detection Algorithm for Malignant Pulmonary Nodules on Chest Radiographs

2018 382 citations Ju Gang Nam, Sunggyun Park et al. Radiology profile →
Development and Validation of a Deep Learning–Based Automated Detection Algorithm for Major Thoracic Diseases on Chest Radiographs

2019 289 citations Eui Jin Hwang, Sunggyun Park et al. JAMA Network Open profile →

Peers

Sunggyun Park

RNMI

PRM

AI

HI

CVPR

Paras Lakhani United States

Jaime Melendez Netherlands

Rick H. H. M. Philipsen Netherlands

Dijia Wu China

Daliang Liu China

Rashid Mazhar Qatar

Yunfei Zha China

Tomoyuki Fujioka Japan

Sangheum Hwang South Korea

Paras Lakhani United States

Sunggyun Park

1.3k ×1.5

RNMI

498 ×1.1

PRM

517 ×1.8

AI

343 ×1.5

HI

157 ×0.9

CVPR

Citations per year, relative to Sunggyun Park Sunggyun Park (= 1×) peers Paras Lakhani

Countries citing papers authored by Sunggyun Park

Since Specialization

Citations

This map shows the geographic impact of Sunggyun Park's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Sunggyun Park with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sunggyun Park more than expected).

Fields of papers citing papers by Sunggyun Park

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sunggyun Park. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sunggyun Park. The network helps show where Sunggyun Park may publish in the future.

Co-authorship network of co-authors of Sunggyun Park

This figure shows the co-authorship network connecting the top 25 collaborators of Sunggyun Park. A scholar is included among the top collaborators of Sunggyun Park based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sunggyun Park. Sunggyun Park is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

12 of 12 papers shown

1.

Park, Sunggyun, et al.. (2021). Evaluation of a deep learning-based computer-aided detection algorithm on chest radiographs. Medicine. 100(16). e25663–e25663. 15 indexed citations

2.

Lee, Jong Hyuk, Hye Young Sun, Sunggyun Park, et al.. (2020). Performance of a Deep Learning Algorithm Compared with Radiologic Interpretation for Lung Cancer Detection on Chest Radiographs in a Health Screening Population. Radiology. 297(3). 687–696. 54 indexed citations

3.

Lee, Jong Hyuk, Sunggyun Park, Eui Jin Hwang, et al.. (2020). Deep learning–based automated detection algorithm for active pulmonary tuberculosis on chest radiographs: diagnostic performance in systematic screening of asymptomatic individuals. European Radiology. 31(2). 1069–1080. 32 indexed citations

4.

Hwang, Eui Jin, Ju Gang Nam, Woo Hyeon Lim, et al.. (2019). Deep Learning for Chest Radiograph Diagnosis in the Emergency Department. Radiology. 293(3). 573–580. 121 indexed citations

5.

Hwang, Eui Jin, Sunggyun Park, Kwang-Nam Jin, et al.. (2019). Development and Validation of a Deep Learning–Based Automated Detection Algorithm for Major Thoracic Diseases on Chest Radiographs. JAMA Network Open. 2(3). e191095–e191095. 289 indexed citations breakdown →

6.

Lee, Jong Hyuk, Sunggyun Park, Eui Jin Hwang, et al.. (2019). Deep-Learning Based Automated Detection Algorithm for Active Pulmonary Tuberculosis on Chest Radiographs: Diagnostic Performance in Systematic Screening of Asymptomatic Individuals. SSRN Electronic Journal.

7.

Nam, Ju Gang, Sunggyun Park, Eui Jin Hwang, et al.. (2018). Development and Validation of Deep Learning–based Automatic Detection Algorithm for Malignant Pulmonary Nodules on Chest Radiographs. Radiology. 290(1). 218–228. 382 indexed citations breakdown →

8.

Hwang, Eui Jin, Sunggyun Park, Kwang-Nam Jin, et al.. (2018). Development and Validation of a Deep Learning–based Automatic Detection Algorithm for Active Pulmonary Tuberculosis on Chest Radiographs. Clinical Infectious Diseases. 69(5). 739–747. 162 indexed citations

9.

Hwang, Eui Jin, Sunggyun Park, Kwang-Nam Jin, et al.. (2018). Development and Validation of a Deep Learning-Based Automated Detection Algorithm for Major Thoracic Diseases on Chest Radiographs. SSRN Electronic Journal. 3 indexed citations

10.

Kim, Kyoung-Kuk, Chi-Guhn Lee, & Sunggyun Park. (2016). Dynamic pricing with ‘BOGO’ promotion in revenue management. International Journal of Production Research. 54(17). 5283–5302. 12 indexed citations

11.

Yoo, Donggeun, et al.. (2015). AttentionNet: Aggregating Weak Directions for Accurate Object Detection. 2659–2667. 114 indexed citations

12.

Yoo, Donggeun, Sunggyun Park, Joon‐Young Lee, & In So Kweon. (2015). Multi-scale pyramid pooling for deep convolutional representation. 71–80. 64 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact