Jong Jin Lee

1.7k total citations
73 papers, 1.2k citations indexed

About

Jong Jin Lee is a scholar working on Surgery, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Jong Jin Lee has authored 73 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Surgery, 24 papers in Radiology, Nuclear Medicine and Imaging and 21 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Jong Jin Lee's work include Medical Imaging Techniques and Applications (15 papers), Radiomics and Machine Learning in Medical Imaging (13 papers) and Thyroid Cancer Diagnosis and Treatment (9 papers). Jong Jin Lee is often cited by papers focused on Medical Imaging Techniques and Applications (15 papers), Radiomics and Machine Learning in Medical Imaging (13 papers) and Thyroid Cancer Diagnosis and Treatment (9 papers). Jong Jin Lee collaborates with scholars based in South Korea, United States and Ethiopia. Jong Jin Lee's co-authors include Sangwon Han, Chong Hyun Suh, Sungmin Woo, Yeon Joo Kim, Jin‐Sook Ryu, Jungsu S. Oh, Jyothi P. Jagannathan, Baek‐Yeol Ryoo, Min‐Hee Ryu and Yoon‐Koo Kang and has published in prestigious journals such as Journal of Clinical Oncology, Radiology and The Lancet Oncology.

In The Last Decade

Jong Jin Lee

70 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jong Jin Lee South Korea 21 482 441 377 196 195 73 1.2k
Antonio De Leo Italy 17 164 0.3× 230 0.5× 63 0.2× 88 0.4× 80 0.4× 101 869
Kinji Nishiyama Japan 22 768 1.6× 727 1.6× 248 0.7× 24 0.1× 56 0.3× 63 1.6k
Masatoyo Nakajo Japan 21 463 1.0× 297 0.7× 755 2.0× 19 0.1× 136 0.7× 90 1.4k
Aparna Balachandran United States 22 614 1.3× 545 1.2× 242 0.6× 59 0.3× 23 0.1× 42 1.6k
Dhakshina Moorthy Ganeshan United States 17 306 0.6× 222 0.5× 112 0.3× 35 0.2× 28 0.1× 32 824
Javier Martínez‐Trufero Spain 20 533 1.1× 1.1k 2.6× 48 0.1× 175 0.9× 105 0.5× 124 2.0k
C.J.H. van de Velde Netherlands 21 604 1.3× 389 0.9× 108 0.3× 72 0.4× 64 0.3× 39 1.5k
Lourdes R. Ylagan United States 20 485 1.0× 289 0.7× 64 0.2× 36 0.2× 192 1.0× 40 1.1k
Antoine Schernberg France 19 349 0.7× 424 1.0× 780 2.1× 21 0.1× 24 0.1× 61 1.6k
Yasemin Özlük Türkiye 18 270 0.6× 280 0.6× 76 0.2× 13 0.1× 154 0.8× 118 1.0k

Countries citing papers authored by Jong Jin Lee

Since Specialization
Citations

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

Fields of papers citing papers by Jong Jin Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jong Jin Lee. 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 Jong Jin Lee. The network helps show where Jong Jin Lee may publish in the future.

Co-authorship network of co-authors of Jong Jin Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Jong Jin Lee. A scholar is included among the top collaborators of Jong Jin Lee 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 Jong Jin Lee. Jong Jin Lee 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.
Han, Sangwon, et al.. (2023). Performance of deep learning models for response evaluation on whole-body bone scans in prostate cancer. Annals of Nuclear Medicine. 37(12). 685–694. 2 indexed citations
2.
Kang, Ho, Jong Jin Lee, Seung Won Choi, et al.. (2021). Radiological assessment schedule for 1p/19q-codeleted gliomas during the surveillance period using parametric modeling. Neuro-Oncology Advances. 3(1). vdab069–vdab069.
4.
Lee, Jong Jin, et al.. (2020). Deep learning detection of prostate cancer recurrence with 18F-FACBC (fluciclovine, Axumin®) positron emission tomography. European Journal of Nuclear Medicine and Molecular Imaging. 47(13). 2992–2997. 21 indexed citations
6.
Lee, Jong Jin, et al.. (2018). A Comparison of the Accuracy of Different Single Plasma Sample Methods for Measuring Glomerular Filtration Rate Using 51Cr-EDTA in Children. Nuclear Medicine and Molecular Imaging. 52(4). 293–302. 1 indexed citations
7.
Han, Sangwon, Sungmin Woo, Chong Hyun Suh, et al.. (2018). A systematic review of the prognostic value of texture analysis in 18F-FDG PET in lung cancer. Annals of Nuclear Medicine. 32(9). 602–610. 26 indexed citations
9.
10.
Kim, Mijin, Won Gu Kim, Suyeon Park, et al.. (2016). Initial Size of Metastatic Lesions Is Best Prognostic Factor in Patients with Metastatic Differentiated Thyroid Carcinoma Confined to the Lung. Thyroid. 27(1). 49–58. 17 indexed citations
11.
Lee, Hyun Ju, Jeong‐Yeol Park, Jong Jin Lee, et al.. (2016). Comparison of MRI and 18F-FDG PET/CT in the preoperative evaluation of uterine carcinosarcoma. Gynecologic Oncology. 140(3). 409–414. 25 indexed citations
12.
Lee, Suk Hyun, et al.. (2016). Metformin discontinuation less than 72 h is suboptimal for F-18 FDG PET/CT interpretation of the bowel. Annals of Nuclear Medicine. 30(9). 629–636. 17 indexed citations
13.
Lee, Suk Hyun, Sangwon Han, Hyo Sang Lee, et al.. (2015). Association Between 18F-FDG Avidity and the BRAF Mutation in Papillary Thyroid Carcinoma. Nuclear Medicine and Molecular Imaging. 50(1). 38–45. 14 indexed citations
14.
Lee, Seung Jin, Jeong Seok Yeo, Eun Jung Lee, et al.. (2014). Thymidine phosphorylase influences [18F]fluorothymidine uptake in cancer cells and patients with non-small cell lung cancer. European Journal of Nuclear Medicine and Molecular Imaging. 41(7). 1327–1335. 13 indexed citations
15.
Song, Ho-Young, Jong Woo Kim, Jin Hyoung Kim, et al.. (2013). Additional gastroduodenal stent placement: retrospective evaluation of 68 consecutive patients with malignant gastroduodenal obstruction. Acta Radiologica. 54(8). 944–948. 10 indexed citations
16.
Kang, Yoon‐Koo, Min‐Hee Ryu, Changhoon Yoo, et al.. (2013). Resumption of imatinib to control metastatic or unresectable gastrointestinal stromal tumours after failure of imatinib and sunitinib (RIGHT): a randomised, placebo-controlled, phase 3 trial. The Lancet Oncology. 14(12). 1175–1182. 132 indexed citations
17.
Im, Hyung‐Jun, Yu Kyeong Kim, Yong Il Kim, et al.. (2012). Usefulness of Combined Metabolic–Volumetric Indices of 18F-FDG PET/CT for the Early Prediction of Neoadjuvant Chemotherapy Outcomes in Breast Cancer. Nuclear Medicine and Molecular Imaging. 47(1). 36–43. 37 indexed citations
18.
Lee, Jong Jin, Dinesh Shetty, Yun‐Sang Lee, et al.. (2011). Evaluation of 111In-labeled macrocyclic chelator-amino acid derivatives for cancer imaging. Nuclear Medicine and Biology. 39(3). 325–333. 5 indexed citations
19.
Kim, Yong Il, Jong Jin Lee, Jin Ho Paik, Yu Kyeong Kim, & Sang Eun Kim. (2011). Detection of Thyroid Metastasis of Renal Transitional Cell Carcinoma Using FDG PET/CT. Nuclear Medicine and Molecular Imaging. 45(2). 149–151. 2 indexed citations
20.
Choi, Seung Hong, Woo Kyung Moon, Kyu Ri Son, et al.. (2007). Lymph Node Metastasis: Ultrasmall Superparamagnetic Iron Oxide–enhanced MR Imaging versus PET/CT in a Rabbit Model. Radiology. 242(1). 137–143. 28 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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