Seonwook Park

1.6k total citations
24 papers, 437 citations indexed

About

Seonwook Park is a scholar working on Radiology, Nuclear Medicine and Imaging, Oncology and Cancer Research. According to data from OpenAlex, Seonwook Park has authored 24 papers receiving a total of 437 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Radiology, Nuclear Medicine and Imaging, 11 papers in Oncology and 9 papers in Cancer Research. Recurrent topics in Seonwook Park's work include Radiomics and Machine Learning in Medical Imaging (15 papers), Cancer Immunotherapy and Biomarkers (10 papers) and Cancer Genomics and Diagnostics (8 papers). Seonwook Park is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (15 papers), Cancer Immunotherapy and Biomarkers (10 papers) and Cancer Genomics and Diagnostics (8 papers). Seonwook Park collaborates with scholars based in South Korea, United States and Hong Kong. Seonwook Park's co-authors include Otmar Hilliges, Xucong Zhang, Andreas Bulling, Sérgio Pereira, Marc Pollefeys, Thomas Schöps, Dong‐Geun Yoo, Mingu Kang, Chan‐Young Ock and Soo Ick Cho and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and European Journal of Cancer.

In The Last Decade

Seonwook Park

24 papers receiving 428 citations

Peers

Seonwook Park

RNMI

CVPR

ONCOL

Nianyi Li United States

Guangzhe Zhao China

Xiao Jin China

Changyang Li Australia

Wenming Tan China

Kuan Tian China

Bin Xie China

Raphael Pelossof United States

Ujjwal Baid India

Iván González-Díaz Spain

Nianyi Li United States

Seonwook Park

68 ×0.4

RNMI

615 ×4.8

CVPR

78 ×0.6

71 ×0.7

24 ×0.2

ONCOL

Citations per year, relative to Seonwook Park Seonwook Park (= 1×) peers Nianyi Li

Countries citing papers authored by Seonwook Park

Since Specialization

Citations

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

Fields of papers citing papers by Seonwook Park

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Seonwook Park

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

All Works

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20 of 20 papers shown

Kim, Hyojin, Seokhwi Kim, Sangjoon Choi, et al.. (2024). Clinical Validation of Artificial Intelligence–Powered PD-L1 Tumor Proportion Score Interpretation for Immune Checkpoint Inhibitor Response Prediction in Non–Small Cell Lung Cancer. JCO Precision Oncology. 8(8). e2300556–e2300556. 12 indexed citations

Lee, Kyu Sang, Soo Ick Cho, Seonwook Park, et al.. (2024). An artificial intelligence‐powered PD‐L1 combined positive score (CPS) analyser in urothelial carcinoma alleviating interobserver and intersite variability. Histopathology. 85(1). 81–91. 5 indexed citations

Brattoli, Biagio, Taebum Lee, Wonkyung Jung, et al.. (2024). A universal immunohistochemistry analyzer for generalizing AI-driven assessment of immunohistochemistry across immunostains and cancer types. npj Precision Oncology. 8(1). 277–277. 4 indexed citations

Jung, Minsun, Soo Ick Cho, Sangwon Shin, et al.. (2024). Augmented interpretation of HER2, ER, and PR in breast cancer by artificial intelligence analyzer: enhancing interobserver agreement through a reader study of 201 cases. Breast Cancer Research. 26(1). 31–31. 14 indexed citations

Lim, Yoojoo, Chan‐Young Ock, Gahee Park, et al.. (2023). Artificial intelligence‐powered spatial analysis of tumor‐infiltrating lymphocytes as a predictive biomarker for axitinib in adenoid cystic carcinoma. Head & Neck. 45(12). 3086–3095. 5 indexed citations

Choi, Sangjoon, Soo Ick Cho, Taebum Lee, et al.. (2023). Deep learning model improves tumor-infiltrating lymphocyte evaluation and therapeutic response prediction in breast cancer. npj Breast Cancer. 9(1). 71–71. 23 indexed citations

Lim, Yoojoo, Hyeon Jeong Oh, Sanghoon Song, et al.. (2023). Artificial intelligence-powered spatial analysis of tumor-infiltrating lymphocytes for prediction of prognosis in resected colon cancer. npj Precision Oncology. 7(1). 124–124. 18 indexed citations

Lim, Yoojoo, Jin Ho Choi, Hye Min Kim, et al.. (2023). Artificial intelligence (AI) –powered spatial analysis of tumor-infiltrating lymphocytes (TILs) for prediction of prognosis in resectable pancreatic adenocarcinoma (PDAC).. Journal of Clinical Oncology. 41(16_suppl). 4162–4162. 1 indexed citations

Lee, Taebum, Soo Ick Cho, Sangjoon Choi, et al.. (2023). Performance validation of an artificial intelligence-powered PD-L1 combined positive score analyzer in six cancer types.. Journal of Clinical Oncology. 41(16_suppl). e13553–e13553. 2 indexed citations

10.

Park, Seonwook, et al.. (2023). EFE: End-to-end Frame-to-Gaze Estimation. Research Repository (Delft University of Technology). 2688–2697. 12 indexed citations

11.

Kang, Mingu, et al.. (2023). Benchmarking Self-Supervised Learning on Diverse Pathology Datasets. 3344–3354. 67 indexed citations

12.

Song, Sanghoon, Wonkyung Jung, Soo Ick Cho, et al.. (2023). Artificial intelligence (AI) –powered H&E whole-slide image (WSI) analysis of tertiary lymphoid structure (TLS) correlates with immune phenotype and related molecular signatures in non–small-cell lung cancer.. Journal of Clinical Oncology. 41(16_suppl). e20520–e20520. 1 indexed citations

13.

Choi, Sangjoon, Soo Ick Cho, Minuk Ma, et al.. (2022). Artificial intelligence–powered programmed death ligand 1 analyser reduces interobserver variation in tumour proportion score for non–small cell lung cancer with better prediction of immunotherapy response. European Journal of Cancer. 170. 17–26. 40 indexed citations

14.

Lee, Hee Jin, Eun Yoon Cho, Yoojoo Lim, et al.. (2022). Artificial intelligence (AI)–powered spatial analysis of tumor-infiltrating lymphocytes (TIL) for prediction of response to neoadjuvant chemotherapy (NAC) in triple-negative breast cancer (TNBC).. Journal of Clinical Oncology. 40(16_suppl). 595–595. 8 indexed citations

15.

Jung, Minsun, Soo Ick Cho, Wonkyung Jung, et al.. (2022). Artificial intelligence-powered human epidermal growth factor receptor 2 (HER2) analyzer in breast cancer as an assistance tool for pathologists to reduce interobserver variation.. Journal of Clinical Oncology. 40(16_suppl). e12543–e12543. 10 indexed citations

16.

Ock, Chan‐Young, Sang-Hoon Song, Gahee Park, et al.. (2021). 830 Artificial intelligence-powered spatial analysis of tumor-infiltrating lymphocytes reveals immune-excluded phenotype related to APOBEC signature and clonal evolution of cancer. SHILAP Revista de lepidopterología. A869–A869. 1 indexed citations

17.

Shen, Jeanne, Taebum Lee, Jun‐Eul Hwang, et al.. (2021). Artificial intelligence-powered spatial analysis of tumor-infiltrating lymphocytes predicts survival after immune checkpoint inhibitor therapy across multiple cancer types.. Journal of Clinical Oncology. 39(15_suppl). 2607–2607. 5 indexed citations

18.

Park, Jeong Hwan, Kyu Sang Lee, Wonkyung Jung, et al.. (2021). Pathologic validation of artificial intelligence-powered prediction of combined positive score of PD-L1 immunohistochemistry in urothelial carcinoma.. Journal of Clinical Oncology. 39(15_suppl). e16518–e16518. 3 indexed citations

19.

Park, Seonwook, Xucong Zhang, Andreas Bulling, & Otmar Hilliges. (2018). Learning to find eye region landmarks for remote gaze estimation in unconstrained settings. arXiv (Cornell University). 1–10. 98 indexed citations

20.

Park, Seonwook, Thomas Schöps, & Marc Pollefeys. (2017). Illumination change robustness in direct visual SLAM. 4523–4530. 62 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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