Ho Sung Kim

8.4k total citations
233 papers, 5.8k citations indexed

About

Ho Sung Kim is a scholar working on Radiology, Nuclear Medicine and Imaging, Genetics and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Ho Sung Kim has authored 233 papers receiving a total of 5.8k indexed citations (citations by other indexed papers that have themselves been cited), including 117 papers in Radiology, Nuclear Medicine and Imaging, 96 papers in Genetics and 45 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Ho Sung Kim's work include Glioma Diagnosis and Treatment (96 papers), MRI in cancer diagnosis (66 papers) and Radiomics and Machine Learning in Medical Imaging (61 papers). Ho Sung Kim is often cited by papers focused on Glioma Diagnosis and Treatment (96 papers), MRI in cancer diagnosis (66 papers) and Radiomics and Machine Learning in Medical Imaging (61 papers). Ho Sung Kim collaborates with scholars based in South Korea, United States and Belarus. Ho Sung Kim's co-authors include Ji Eun Park, Sang Joon Kim, Choong Gon Choi, Seo Young Park, Chong Hyun Suh, Seung Chai Jung, Namkug Kim, Jeong Hoon Kim, Woo Hyun Shim and Jung Youn Kim and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Neurology.

In The Last Decade

Ho Sung Kim

218 papers receiving 5.7k citations

Peers

Ho Sung Kim
Rajan Jain United States
Sung Soo Ahn South Korea
Jonathan H. Sherman United States
Sung‐Hye Park South Korea
Kristen W. Yeom United States
Ji‐hoon Kim South Korea
Ho Sung Kim
Citations per year, relative to Ho Sung Kim Ho Sung Kim (= 1×) peers Philipp Kickingereder

Countries citing papers authored by Ho Sung Kim

Since Specialization
Citations

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

Fields of papers citing papers by Ho Sung Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ho Sung Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Ho Sung Kim. A scholar is included among the top collaborators of Ho Sung 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 Ho Sung Kim. Ho Sung 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.
Park, Ji Eun, Seo Young Park, Seunghee Baek, et al.. (2025). Maximum Resection of Noncontrast-enhanced Tumor at MRI Is a Favorable Prognostic Factor in IDH Wild-Type Glioblastoma. Radiology. 315(2). e241393–e241393.
2.
Kim, Ho Sung, et al.. (2024). Thermal contact resistance measurement between EXG and polyimide substrates under varying pressure and thermal interfacial material. International Journal of Nanotechnology. 21(3). 148–156. 1 indexed citations
3.
Park, Ji Eun, Seon‐Ok Kim, Yong Seo Koo, et al.. (2024). Improving Diagnostic Performance of MRI for Temporal Lobe Epilepsy With Deep Learning-Based Image Reconstruction in Patients With Suspected Focal Epilepsy. Korean Journal of Radiology. 25(4). 374–374. 10 indexed citations
4.
Kang, Koung Mi, Yunhee Choi, Ji Eun Park, et al.. (2024). MRI Scoring Systems for Predicting Isocitrate Dehydrogenase Mutation and Chromosome 1p/19q Codeletion in Adult-type Diffuse Glioma Lacking Contrast Enhancement. Radiology. 311(2). e233120–e233120. 10 indexed citations
5.
Park, Ji Eun, Namkug Kim, Young‐Hoon Kim, et al.. (2024). Generative AI in glioma: Ensuring diversity in training image phenotypes to improve diagnostic performance for IDH mutation prediction. Neuro-Oncology. 26(6). 1124–1135. 11 indexed citations
6.
Park, Ji Eun, Ho‐Su Lee, Shinkyo Yoon, et al.. (2024). Mapping tumor habitats in isocitrate dehydrogenase -wild type glioblastoma: Integrating MRI, pathologic, and RNA data from the Ivy Glioblastoma Atlas Project. Neuro-Oncology. 27(1). 291–301. 1 indexed citations
7.
Park, Yae Won, Ji Eun Park, Sung Soo Ahn, et al.. (2023). Qualitative and Quantitative Magnetic Resonance Imaging Phenotypes May Predict CDKN2A/B Homozygous Deletion Status in Isocitrate Dehydrogenase-Mutant Astrocytomas: A Multicenter Study. Korean Journal of Radiology. 24(2). 133–133. 18 indexed citations
8.
Park, Ji Eun, et al.. (2023). Imaging-Based Versus Pathologic Survival Stratifications of Diffuse Glioma According to the 2021 WHO Classification System. Korean Journal of Radiology. 24(8). 772–772. 2 indexed citations
9.
Kwon, Ji Hye, Seung Soo Lee, Jee Seok Yoon, et al.. (2021). Liver-to-Spleen Volume Ratio Automatically Measured on CT Predicts Decompensation in Patients with B Viral Compensated Cirrhosis. Korean Journal of Radiology. 22(12). 1985–1985. 15 indexed citations
10.
Kim, Pyeong Hwa, Chong Hyun Suh, Ho Sung Kim, et al.. (2020). Immune Checkpoint Inhibitor with or without Radiotherapy in Melanoma Patients with Brain Metastases: A Systematic Review and Meta-Analysis. Korean Journal of Radiology. 22(4). 584–584. 20 indexed citations
11.
Ahn, Yura, Jee Seok Yoon, Seung Soo Lee, et al.. (2020). Deep Learning Algorithm for Automated Segmentation and Volume Measurement of the Liver and Spleen Using Portal Venous Phase Computed Tomography Images. Korean Journal of Radiology. 21(8). 987–987. 48 indexed citations
12.
Kim, Minjae, Chong Hyun Suh, Sang Min Lee, et al.. (2020). Diagnostic Yield of Staging Brain MRI in Patients with Newly Diagnosed Non–Small Cell Lung Cancer. Radiology. 297(2). 419–427. 20 indexed citations
13.
Shin, Youngbin, Kyung Won Kim, Yu Sub Sung, et al.. (2019). A Good Practice–Compliant Clinical Trial Imaging Management System for Multicenter Clinical Trials: Development and Validation Study. JMIR Medical Informatics. 7(3). e14310–e14310. 11 indexed citations
14.
Suh, Chong Hyun, Ho Sung Kim, Wooyul Paik, et al.. (2019). False-Positive Measurement at 2-Hydroxyglutarate MR Spectroscopy in Isocitrate Dehydrogenase Wild-Type Glioblastoma: A Multifactorial Analysis. Radiology. 291(3). 752–762. 28 indexed citations
15.
Paik, Wooyul, Ho Sung Kim, Choong Gon Choi, & Sang Joon Kim. (2016). Pre-Operative Perfusion Skewness and Kurtosis Are Potential Predictors of Progression-Free Survival after Partial Resection of Newly Diagnosed Glioblastoma. Korean Journal of Radiology. 17(1). 117–117. 8 indexed citations
16.
Chung, Mi Sun, Seung Chai Jung, Ho Sung Kim, et al.. (2016). Comparison of High-Resolution MR Imaging and Digital Subtraction Angiography for the Characterization and Diagnosis of Intracranial Artery Disease. American Journal of Neuroradiology. 37(12). 2245–2250. 26 indexed citations
17.
Park, Ji Eun, Ho Sung Kim, Kye Jin Park, et al.. (2015). Pre- and Posttreatment Glioma: Comparison of Amide Proton Transfer Imaging with MR Spectroscopy for Biomarkers of Tumor Proliferation. Radiology. 278(2). 514–523. 89 indexed citations
18.
Kim, Eun Jin, Ji Man Hong, Sung Eun Lee, et al.. (2011). Conventional Enhancement CT: A Valuable Tool for Evaluating Pial Collateral Flow in Acute Ischemic Stroke. Cerebrovascular Diseases. 31(4). 346–352. 33 indexed citations
19.
Shin, Choong Ho, Ho Sung Kim, Sei Won Yang, & Jung Yun Choi. (2001). Clinical Characteristics of Williams Syndrome. Korean Journal of Pediatrics. 44(4). 443–449.
20.
Kim, Hye Soon, et al.. (1997). Transcatheter Coil Closure of a Congenital Coronary Arterial Fistula. Korean Journal of Pediatrics. 40(5). 730–734.

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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