Kum Ju Chae

1.3k total citations
69 papers, 737 citations indexed

About

Kum Ju Chae is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Biomedical Engineering. According to data from OpenAlex, Kum Ju Chae has authored 69 papers receiving a total of 737 indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Pulmonary and Respiratory Medicine, 20 papers in Radiology, Nuclear Medicine and Imaging and 9 papers in Biomedical Engineering. Recurrent topics in Kum Ju Chae's work include Lung Cancer Diagnosis and Treatment (22 papers), Chronic Obstructive Pulmonary Disease (COPD) Research (21 papers) and Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (20 papers). Kum Ju Chae is often cited by papers focused on Lung Cancer Diagnosis and Treatment (22 papers), Chronic Obstructive Pulmonary Disease (COPD) Research (21 papers) and Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (20 papers). Kum Ju Chae collaborates with scholars based in South Korea, United States and Ethiopia. Kum Ju Chae's co-authors include Gong Yong Jin, Jin Mo Goo, Hyemi Choi, Chang Hyun Lee, Sanghun Choi, Jong Eun Lee, Woo Jin Kim, Myoung Ja Chung, Yun‐Hyeon Kim and Chang Min Park and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and The Science of The Total Environment.

In The Last Decade

Kum Ju Chae

61 papers receiving 718 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Kum Ju Chae South Korea 17 477 230 101 62 44 69 737
Christian Blüthgen Switzerland 15 180 0.4× 320 1.4× 156 1.5× 55 0.9× 20 0.5× 38 565
So Hyeon Bak South Korea 15 517 1.1× 331 1.4× 164 1.6× 52 0.8× 12 0.3× 53 806
Farbod N. Rahaghi United States 16 663 1.4× 234 1.0× 63 0.6× 58 0.9× 13 0.3× 56 960
Florian Prayer Austria 11 240 0.5× 413 1.8× 127 1.3× 51 0.8× 23 0.5× 36 646
Victorine V. Muse United States 17 399 0.8× 500 2.2× 200 2.0× 76 1.2× 16 0.4× 35 890
Dharshan Vummidi United States 11 352 0.7× 218 0.9× 25 0.2× 75 1.2× 41 0.9× 22 653
Samuel Y. Ash United States 18 735 1.5× 207 0.9× 49 0.5× 52 0.8× 19 0.4× 49 1.0k
Mitsuko Tsubamoto Japan 18 581 1.2× 360 1.6× 137 1.4× 153 2.5× 17 0.4× 36 976
Sebastian Röhrich Austria 15 239 0.5× 404 1.8× 190 1.9× 189 3.0× 20 0.5× 38 826
Myrna C. B. Godoy United States 16 400 0.8× 332 1.4× 35 0.3× 131 2.1× 108 2.5× 41 831

Countries citing papers authored by Kum Ju Chae

Since Specialization
Citations

This map shows the geographic impact of Kum Ju Chae'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 Kum Ju Chae with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kum Ju Chae more than expected).

Fields of papers citing papers by Kum Ju Chae

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kum Ju Chae. 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 Kum Ju Chae. The network helps show where Kum Ju Chae may publish in the future.

Co-authorship network of co-authors of Kum Ju Chae

This figure shows the co-authorship network connecting the top 25 collaborators of Kum Ju Chae. A scholar is included among the top collaborators of Kum Ju Chae 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 Kum Ju Chae. Kum Ju Chae is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Lee, Jong Hyuk, Kum Ju Chae, Michael T. Lu, et al.. (2025). External Testing of a Deep Learning Model for Lung Cancer Risk from Low-Dose Chest CT. Radiology. 316(2). e243393–e243393.
2.
Kim, Youlim, Hyun Jung Lee, Hyeon‐Kyoung Koo, et al.. (2025). Kernel Conversion Improves the Correlation between the Extent of Emphysema and Clinical Parameters in Chronic Obstructive Pulmonary Disease: A Multicenter Cohort Study. Tuberculosis & respiratory diseases. 88(2). 303–309. 1 indexed citations
3.
Chae, Kum Ju, et al.. (2025). Multiscale simulation of respiratory airflow using physiologically consistent geometry and boundary conditions in OpenFOAM. Computers in Biology and Medicine. 198(Pt A). 111131–111131.
4.
Lee, Jong Eun, Kum Ju Chae, Kwang Nam Jin, et al.. (2024). Diagnostic performance of radiologists in distinguishing post-COVID-19 residual abnormalities from interstitial lung abnormalities. European Radiology. 35(4). 2265–2274.
5.
Chae, Kum Ju, Hye Jeon Hwang, Rosane Duarte Achcar, et al.. (2024). Central Role of CT in Management of Pulmonary Fibrosis. Radiographics. 44(6). e230165–e230165. 4 indexed citations
6.
Humphries, Stephen M., David Baraghoshi, Matthew Strand, et al.. (2024). Deep Learning Classification of Usual Interstitial Pneumonia Predicts Outcomes. American Journal of Respiratory and Critical Care Medicine. 209(9). 1121–1131. 18 indexed citations
7.
Chae, Kum Ju, Jong Eun Lee, Masahiro Yanagawa, et al.. (2024). Optimizing prone CT use for suspected interstitial lung abnormalities. European Radiology. 35(6). 3021–3029.
8.
Cui, Xinguang, Ching‐Long Lin, Stephen Baek, et al.. (2024). Human-airway surface mesh smoothing based on graph convolutional neural networks. Computer Methods and Programs in Biomedicine. 246. 108061–108061. 4 indexed citations
9.
Kim, Woo Jin, et al.. (2023). An unsupervised image registration method employing chest computed tomography images and deep neural networks. Computers in Biology and Medicine. 154. 106612–106612. 23 indexed citations
10.
11.
Chae, Kum Ju, Soyeoun Lim, Joon Beom Seo, et al.. (2023). Interstitial Lung Abnormalities at CT in the Korean National Lung Cancer Screening Program: Prevalence and Deep Learning–based Texture Analysis. Radiology. 307(4). e222828–e222828. 30 indexed citations
12.
Jin, Gong Yong, et al.. (2023). Quantitative CT Analysis Based on Smoking Habits and Chronic Obstructive Pulmonary Disease in Patients with Normal Chest CT. SHILAP Revista de lepidopterología. 84(4). 900–900. 2 indexed citations
13.
Chae, Kum Ju, Myoung Ja Chung, Gong Yong Jin, et al.. (2022). Radiologic-pathologic correlation of interstitial lung abnormalities and predictors for progression and survival. European Radiology. 32(4). 2713–2723. 35 indexed citations
14.
Lee, Jong Eun, Kum Ju Chae, Young Ju Suh, et al.. (2022). Prevalence and Long-term Outcomes of CT Interstitial Lung Abnormalities in a Health Screening Cohort. Radiology. 306(2). e221172–e221172. 30 indexed citations
15.
16.
Jeong, Jae Seok, et al.. (2021). An Unusual Manifestation of Rapidly Progressing Granulomatosis with Polyangiitis Involving Uterine Adnexa and Lung. American Journal of Respiratory and Critical Care Medicine. 203(11). 1431–1432. 1 indexed citations
17.
Chae, Kum Ju, Gong Yong Jin, Jiwoong Choi, et al.. (2021). Generation-based study of airway remodeling in smokers with normal-looking CT with normalization to control inter-subject variability. European Journal of Radiology. 138. 109657–109657. 10 indexed citations
18.
Chae, Kum Ju, Gong Yong Jin, Jin Mo Goo, & Myoung Ja Chung. (2020). Interstitial Lung Abnormalities: What Radiologists Should Know. Korean Journal of Radiology. 22(3). 454–454. 16 indexed citations
19.
Wang, Yi, Hao Zhang, Kum Ju Chae, et al.. (2020). Novel convolutional neural network architecture for improved pulmonary nodule classification on computed tomography. Multidimensional Systems and Signal Processing. 31(3). 1163–1183. 20 indexed citations
20.
Yoon, Soon Ho, Sang Min Lee, Chul Hwan Park, et al.. (2020). 2020 Clinical Practice Guideline for Percutaneous Transthoracic Needle Biopsy of Pulmonary Lesions: A Consensus Statement and Recommendations of the Korean Society of Thoracic Radiology. Korean Journal of Radiology. 22(2). 263–263. 41 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.

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