Hyemin Um

508 total citations
10 papers, 354 citations indexed

About

Hyemin Um is a scholar working on Radiology, Nuclear Medicine and Imaging, Genetics and Biomedical Engineering. According to data from OpenAlex, Hyemin Um has authored 10 papers receiving a total of 354 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Radiology, Nuclear Medicine and Imaging, 5 papers in Genetics and 3 papers in Biomedical Engineering. Recurrent topics in Hyemin Um's work include Radiomics and Machine Learning in Medical Imaging (9 papers), Glioma Diagnosis and Treatment (5 papers) and Advanced X-ray and CT Imaging (3 papers). Hyemin Um is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (9 papers), Glioma Diagnosis and Treatment (5 papers) and Advanced X-ray and CT Imaging (3 papers). Hyemin Um collaborates with scholars based in United States, Netherlands and United Kingdom. Hyemin Um's co-authors include Harini Veeraraghavan, Robert J. Young, Florent Tixier, Joseph O. Deasy, Aditya Apte, Aditi Iyer, Jung Hun Oh, Emiliano Spezi, Mireia Crispin‐Ortuzar and Maria Thor and has published in prestigious journals such as Journal of Clinical Oncology, Physics in Medicine and Biology and Medical Physics.

In The Last Decade

Hyemin Um

10 papers receiving 352 citations

Peers

Hyemin Um
Nabil Elshafeey United States
Julián Pérez-Beteta Spain
Jeong Hoon Kim South Korea
Sara Ahmed United States
Martijn P. A. Starmans Netherlands
Srishti Abrol United States
Guoqiang Yang China
Youngheun Jo South Korea
Ginu Thomas United States
G. Klausner France
Nabil Elshafeey United States
Hyemin Um
Citations per year, relative to Hyemin Um Hyemin Um (= 1×) peers Nabil Elshafeey

Countries citing papers authored by Hyemin Um

Since Specialization
Citations

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

Fields of papers citing papers by Hyemin Um

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hyemin Um. 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 Hyemin Um. The network helps show where Hyemin Um may publish in the future.

Co-authorship network of co-authors of Hyemin Um

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

All Works

10 of 10 papers shown
1.
Li, Chengnan, et al.. (2024). Leveraging radiomics and machine learning to differentiate radiation necrosis from recurrence in patients with brain metastases. Journal of Neuro-Oncology. 168(2). 307–316. 5 indexed citations
2.
McKenney, Anna Sophia, Emily S. Weg, Tejus Bale, et al.. (2022). Radiomic Analysis to Predict Histopathologically Confirmed Pseudoprogression in Glioblastoma Patients. Advances in Radiation Oncology. 8(1). 100916–100916. 14 indexed citations
3.
Huang, Raymond Y., Robert J. Young, Benjamin M. Ellingson, et al.. (2020). Volumetric analysis of IDH-mutant lower-grade glioma: a natural history study of tumor growth rates before and after treatment. Neuro-Oncology. 22(12). 1822–1830. 26 indexed citations
4.
Um, Hyemin, et al.. (2019). Impact of image preprocessing on the scanner dependence of multi-parametric MRI radiomic features and covariate shift in multi-institutional glioblastoma datasets. Physics in Medicine and Biology. 64(16). 165011–165011. 84 indexed citations
5.
Tixier, Florent, Hyemin Um, Robert J. Young, & Harini Veeraraghavan. (2019). Reliability of tumor segmentation in glioblastoma: Impact on the robustness of MRI‐radiomic features. Medical Physics. 46(8). 3582–3591. 37 indexed citations
6.
Tixier, Florent, Hyemin Um, Aditi Iyer, et al.. (2019). Preoperative MRI-radiomics features improve prediction of survival in glioblastoma patients over MGMT methylation status alone. Oncotarget. 10(6). 660–672. 38 indexed citations
7.
Bhatia, Ankush, Maxwell Birger, Harini Veeraraghavan, et al.. (2019). MRI radiomic features are associated with survival in melanoma brain metastases treated with immune checkpoint inhibitors. Neuro-Oncology. 21(12). 1578–1586. 46 indexed citations
8.
Apte, Aditya, Aditi Iyer, Mireia Crispin‐Ortuzar, et al.. (2018). Technical Note: Extension of CERR for computational radiomics: A comprehensive MATLAB platform for reproducible radiomics research. Medical Physics. 45(8). 3713–3720. 102 indexed citations
9.
Bhatia, Ankush, Maxwell Birger, Harini Veeraraghavan, et al.. (2018). MRI texture features and outcomes to immune checkpoint inhibitors in melanoma brain metastases.. Journal of Clinical Oncology. 36(15_suppl). 2069–2069. 1 indexed citations
10.
Kim, T. J., et al.. (2016). A Study on Game Bot Detection Using Self-Similarity in MMORPGs. Journal of the Korea Institute of Information Security and Cryptology. 26(1). 93–107. 1 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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2026