Hae Won Kim

1.3k total citations
67 papers, 976 citations indexed

About

Hae Won Kim is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Surgery. According to data from OpenAlex, Hae Won Kim has authored 67 papers receiving a total of 976 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Pulmonary and Respiratory Medicine, 18 papers in Radiology, Nuclear Medicine and Imaging and 13 papers in Surgery. Recurrent topics in Hae Won Kim's work include Radiomics and Machine Learning in Medical Imaging (13 papers), Gastric Cancer Management and Outcomes (11 papers) and Medical Imaging Techniques and Applications (10 papers). Hae Won Kim is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (13 papers), Gastric Cancer Management and Outcomes (11 papers) and Medical Imaging Techniques and Applications (10 papers). Hae Won Kim collaborates with scholars based in South Korea, United States and United Kingdom. Hae Won Kim's co-authors include Kyoung Sook Won, Jong Rack Sohn, Bong‐Il Song, Jeong‐Ho Hong, Byeong‐Cheol Ahn, Jaetae Lee, Sang‐Woo Lee, Shin Young Jeong, Jungsu S. Oh and Hyon‐Ah Yi and has published in prestigious journals such as PLoS ONE, Scientific Reports and International Journal of Molecular Sciences.

In The Last Decade

Hae Won Kim

62 papers receiving 957 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hae Won Kim South Korea 19 261 225 152 142 122 67 976
Lingfei Guo China 17 300 1.1× 164 0.7× 85 0.6× 29 0.2× 139 1.1× 83 837
Qinying Li China 17 46 0.2× 108 0.5× 106 0.7× 84 0.6× 65 0.5× 51 897
Anita Seese Germany 19 484 1.9× 260 1.2× 176 1.2× 104 0.7× 151 1.2× 42 1.2k
Yoshio Ohta Japan 17 38 0.1× 165 0.7× 201 1.3× 68 0.5× 39 0.3× 98 985
Chao‐Hung Wang Taiwan 19 54 0.2× 85 0.4× 201 1.3× 171 1.2× 24 0.2× 37 1.4k
Emmanuelle Canet‐Soulas France 21 317 1.2× 326 1.4× 130 0.9× 27 0.2× 73 0.6× 65 1.3k
Gao‐Jun Teng China 18 143 0.5× 184 0.8× 214 1.4× 89 0.6× 29 0.2× 45 928
Nobuyuki Murakoshi Japan 23 171 0.7× 126 0.6× 158 1.0× 86 0.6× 46 0.4× 79 1.7k
Yohei Nomura Japan 17 53 0.2× 119 0.5× 157 1.0× 24 0.2× 129 1.1× 50 910

Countries citing papers authored by Hae Won Kim

Since Specialization
Citations

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

Fields of papers citing papers by Hae Won Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hae Won Kim. 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 Hae Won Kim. The network helps show where Hae Won Kim may publish in the future.

Co-authorship network of co-authors of Hae Won Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Hae Won Kim. A scholar is included among the top collaborators of Hae Won Kim 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 Hae Won Kim. Hae Won Kim 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.
Hong, Eun Kyoung, et al.. (2025). Multimodal Generative Artificial Intelligence Model for Creating Radiology Reports for Chest Radiographs in Patients Undergoing Tuberculosis Screening. American Journal of Roentgenology. 225(4). e2533059–e2533059.
2.
Yu, Mi-Hee, et al.. (2024). Association between Visceral Adipose Tissue Metabolism and Cerebral Glucose Metabolism in Patients with Cognitive Impairment. International Journal of Molecular Sciences. 25(13). 7479–7479. 5 indexed citations
3.
4.
Lim, Ji Sun, Shin Kim, Hyunsu Lee, et al.. (2024). The Neuroprotective Effect of Therapeutic Hypothermia in Cognitive Impairment of an Ischemia/Reperfusion Injury Mouse Model. Medicina. 60(3). 350–350. 1 indexed citations
5.
6.
Park, Jae Seok, Yong Shik Kwon, Sun Hyo Park, et al.. (2023). Development of lung cancer risk prediction models based on F-18 FDG PET images. Annals of Nuclear Medicine. 37(10). 572–582. 2 indexed citations
7.
Son, Seung Hyun, June Hong Ahn, Kyeong Cheol Shin, Hae Won Kim, & Eunjung Kong. (2023). Brain FDG PET for visualizing the relation between impaired lung function and cognitive decline in lung cancer: a preliminary study. Nuclear Medicine Communications. 44(6). 488–494. 3 indexed citations
8.
Kim, Jae Seung, et al.. (2022). 60 Years of Achievements by KSNM in Neuroimaging Research. Nuclear Medicine and Molecular Imaging. 56(1). 3–16. 1 indexed citations
9.
Hong, Chae Moon, Young Jin Jeong, Hae Won Kim, & Byeong‐Cheol Ahn. (2022). KSNM60 in Nuclear Endocrinology: from the Beginning to the Future. Nuclear Medicine and Molecular Imaging. 56(1). 17–28. 2 indexed citations
10.
Kim, Sung Hoon, Bong‐Il Song, Hae Won Kim, et al.. (2022). Prognostic value of the metabolic score obtained via [18F]FDG PET/CT and a new prognostic staging system for gastric cancer. Scientific Reports. 12(1). 20681–20681. 2 indexed citations
11.
Kim, Tae Hun, Sun Hyo Park, Ilseon Hwang, et al.. (2021). Robust response of pulmonary pleomorphic carcinoma to pembrolizumab and sequential radiotherapy: A case report. Respirology Case Reports. 9(12). e0875–e0875. 3 indexed citations
12.
Kim, Sung Hoon, Bong‐Il Song, Hae Won Kim, & Kyoung Sook Won. (2020). Comparison of Image Quality and Semi-quantitative Measurements with Digital PET/CT and Standard PET/CT from Different Vendors. Nuclear Medicine and Molecular Imaging. 54(5). 233–240. 6 indexed citations
13.
14.
Park, Jae Hyun, et al.. (2019). Comparison of Tc-99m DMSA Renal Planar Scan and SPECT for Detection of Cortical Defects in Infants with Suspected Acute Pyelonephritis. The Indian Journal of Pediatrics. 86(9). 797–802. 11 indexed citations
15.
Kim, Hae Won, Da Hyun Jung, Jie‐Hyun Kim, et al.. (2017). The longest diameter of tumor as a parameter of endoscopic resection in early gastric cancer: In comparison with tumor area. PLoS ONE. 12(12). e0189649–e0189649. 4 indexed citations
16.
Kim, Hae Won, Jie‐Hyun Kim, Jie‐Hyun Kim, et al.. (2017). Additive endoscopic resection may be sufficient for patients with a positive lateral margin after endoscopic resection of early gastric cancer. Gastrointestinal Endoscopy. 86(5). 849–856. 16 indexed citations
17.
Kim, Hae Won, et al.. (2016). Diagnostic accuracy of 18F-FDG PET/CT for detecting synchronous advanced colorectal neoplasia in patients with gastric cancer. Medicine. 95(36). e4741–e4741. 6 indexed citations
18.
Kim, Hae Won, et al.. (2016). A rare case of coronary fistula evaluated by first-pass radionuclide angiography.. PubMed. 19(2). 167–9.
19.
Kim, Sung Hoon, et al.. (2014). Correlation of Primary Tumor FDG Uptake with Clinicopathologic Prognostic Factors in Invasive Ductal Carcinoma of the Breast. Nuclear Medicine and Molecular Imaging. 49(1). 19–25. 18 indexed citations
20.
Kim, Hae Won, Jung Eun Kim, Yong Hyun Jeon, et al.. (2013). Enhancement of Natural Killer Cell Cytotoxicity by Sodium/Iodide Symporter Gene-Mediated Radioiodine Pretreatment in Breast Cancer Cells. PLoS ONE. 8(8). e70194–e70194. 17 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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