Ja‐Young Choi

1.4k total citations
39 papers, 934 citations indexed

About

Ja‐Young Choi is a scholar working on Surgery, Rheumatology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Ja‐Young Choi has authored 39 papers receiving a total of 934 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Surgery, 12 papers in Rheumatology and 9 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Ja‐Young Choi's work include Knee injuries and reconstruction techniques (5 papers), Total Knee Arthroplasty Outcomes (5 papers) and Osteoarthritis Treatment and Mechanisms (4 papers). Ja‐Young Choi is often cited by papers focused on Knee injuries and reconstruction techniques (5 papers), Total Knee Arthroplasty Outcomes (5 papers) and Osteoarthritis Treatment and Mechanisms (4 papers). Ja‐Young Choi collaborates with scholars based in South Korea, Ethiopia and Puerto Rico. Ja‐Young Choi's co-authors include Sung Hwan Hong, Heung Sik Kang, Joon Woo Lee, Young Hwan Koh, Heung Sik Kang, Hye Won Chung, Jung-Ah Choi, Hye Jin Yoo, Jung‐Ah Choi and Jee Won Chai and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Ja‐Young Choi

36 papers receiving 903 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ja‐Young Choi South Korea 18 367 339 213 207 155 39 934
Francesca D. Beaman United States 20 542 1.5× 335 1.0× 238 1.1× 146 0.7× 144 0.9× 35 1.1k
Bernhard Tins United Kingdom 20 653 1.8× 459 1.4× 163 0.8× 85 0.4× 197 1.3× 55 1.1k
Paolo Spinnato Italy 19 440 1.2× 386 1.1× 481 2.3× 148 0.7× 169 1.1× 120 1.2k
Wook Jin South Korea 22 842 2.3× 509 1.5× 136 0.6× 177 0.9× 293 1.9× 90 1.6k
Hakan Ilaslan United States 20 541 1.5× 470 1.4× 494 2.3× 99 0.5× 151 1.0× 74 1.2k
Kambiz Motamedi United States 23 879 2.4× 629 1.9× 370 1.7× 113 0.5× 214 1.4× 62 1.5k
Jang Gyu South Korea 19 478 1.3× 178 0.5× 100 0.5× 285 1.4× 222 1.4× 81 1.0k
G Y el-Khoury United States 18 622 1.7× 494 1.5× 203 1.0× 68 0.3× 231 1.5× 35 1.1k
Caroline Parlier‐Cuau France 14 365 1.0× 330 1.0× 191 0.9× 49 0.2× 154 1.0× 43 744
Michael G. Fox United States 18 658 1.8× 270 0.8× 108 0.5× 81 0.4× 360 2.3× 69 1.0k

Countries citing papers authored by Ja‐Young Choi

Since Specialization
Citations

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

Fields of papers citing papers by Ja‐Young Choi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ja‐Young Choi. 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 Ja‐Young Choi. The network helps show where Ja‐Young Choi may publish in the future.

Co-authorship network of co-authors of Ja‐Young Choi

This figure shows the co-authorship network connecting the top 25 collaborators of Ja‐Young Choi. A scholar is included among the top collaborators of Ja‐Young Choi 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 Ja‐Young Choi. Ja‐Young Choi 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.
2.
Yoo, Hye Jin, Dominik Nickel, Gregor Koerzdoerfer, et al.. (2023). Feasibility and clinical usefulness of deep learning-accelerated MRI for acute painful fracture patients wearing a splint: A prospective comparative study. PLoS ONE. 18(6). e0287903–e0287903. 1 indexed citations
3.
Yoo, Hye Jin, Young Jae Kim, Hyunsook Hong, et al.. (2022). Deep learning–based fully automated body composition analysis of thigh CT: comparison with DXA measurement. European Radiology. 32(11). 7601–7611. 9 indexed citations
4.
Chae, Hee‐Dong, et al.. (2022). Improved diagnostic performance of plain radiography for cervical ossification of the posterior longitudinal ligament using deep learning. PLoS ONE. 17(4). e0267643–e0267643. 5 indexed citations
5.
6.
Kim, Bo Ram, Hee‐Dong Chae, Sung‐Joon Ye, et al.. (2022). Deep Radiomics–based Approach to the Diagnosis of Osteoporosis Using Hip Radiographs. Radiology Artificial Intelligence. 4(4). e210212–e210212. 13 indexed citations
7.
Kang, Ji Hee, Kyoung Bun Lee, Hye Jin Yoo, et al.. (2020). Ultrasound and Magnetic Resonance Imaging Features of Calcifying Aponeurotic Fibromas. Journal of Ultrasound in Medicine. 39(7). 1299–1306. 8 indexed citations
8.
Yoo, Hye Jin, Sung Hwan Hong, Dong Hyun Kim, et al.. (2016). Measurement of fat content in vertebral marrow using a modified dixon sequence to differentiate benign from malignant processes. Journal of Magnetic Resonance Imaging. 45(5). 1534–1544. 63 indexed citations
9.
Chai, Jee Won, Sung Hwan Hong, Ja‐Young Choi, et al.. (2010). Radiologic Diagnosis of Osteoid Osteoma: From Simple to Challenging Findings. Radiographics. 30(3). 737–749. 158 indexed citations
10.
Yoo, Hye Jin, Jung-Ah Choi, Jin‐Haeng Chung, et al.. (2009). Angioleiomyoma in Soft Tissue of Extremities: MRI Findings. American Journal of Roentgenology. 192(6). W291–W294. 50 indexed citations
11.
Park, Eun‐Ah, Sung Hwan Hong, Kwang Gi Kim, et al.. (2009). Experimental Bone Biopsies Using Two Bone Biopsy Needles. Academic Radiology. 16(3). 332–340. 4 indexed citations
12.
Myung, Jae Sung, Joon Woo Lee, Jin S. Yeom, et al.. (2008). MR Diskography and CT Diskography with Gadodiamide–Iodinated Contrast Mixture for the Diagnosis of Foraminal Impingement. American Journal of Roentgenology. 191(3). 710–715. 2 indexed citations
13.
Moon, Sung Gyu, Sung Hwan Hong, Ja‐Young Choi, et al.. (2008). Metal Artifact Reduction by the Alteration of Technical Factors in Multidetector Computed Tomography. Journal of Computer Assisted Tomography. 32(4). 630–633. 38 indexed citations
14.
Lee, Joon Woo, Kyung Seok Park, Jae Hyoung Kim, et al.. (2008). Diffusion Tensor Imaging in Idiopathic Acute Transverse Myelitis. American Journal of Roentgenology. 191(2). W52–W57. 27 indexed citations
15.
Kim, Na Ra, Ja‐Young Choi, Sung Hwan Hong, et al.. (2008). “MR Corner Sign”: Value for Predicting Presence of Ankylosing Spondylitis. American Journal of Roentgenology. 191(1). 124–128. 39 indexed citations
16.
Choi, Ja‐Young, Sung Hwan Hong, Han‐Soo Kim, et al.. (2005). Resorption of Osteochondroma by Accompanying Pseudoaneurysm. American Journal of Roentgenology. 185(2). 394–396. 14 indexed citations
17.
Park, Eun‐Ah, et al.. (2004). Glomangiomatosis: magnetic resonance imaging findings in three cases. Skeletal Radiology. 34(2). 108–111. 17 indexed citations
18.
Goo, Jin Mo, Ja‐Young Choi, Jung-Gi Im, et al.. (2004). Effect of Monitor Luminance and Ambient Light on Observer Performance in Soft-Copy Reading of Digital Chest Radiographs. Radiology. 232(3). 762–766. 58 indexed citations
19.
Hong, Sung Hwan, et al.. (2003). Grading of Anterior Cruciate Ligament Injury. Journal of Computer Assisted Tomography. 27(5). 814–819. 81 indexed citations
20.
Choi, Ja‐Young, Seung Hwan Kim, & Sun Min Kim. (2002). Double-blind ureteral duplication: report of two cases. European Radiology. 12(S3). S136–S139. 5 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

Breakdown of academic impact, for papers by Francesca D. Beaman Breakdown of academic impact, for papers by Bernhard Tins Breakdown of academic impact, for papers by Paolo Spinnato Breakdown of academic impact, for papers by Wook Jin Breakdown of academic impact, for papers by Hakan Ilaslan Breakdown of academic impact, for papers by Kambiz Motamedi Breakdown of academic impact, for papers by Jang Gyu Breakdown of academic impact, for papers by G Y el-Khoury Breakdown of academic impact, for papers by Caroline Parlier‐Cuau Breakdown of academic impact, for papers by Michael G. Fox
Rankless by CCL
2026