Minuk Ma

767 total citations
14 papers, 235 citations indexed

About

Minuk Ma is a scholar working on Radiology, Nuclear Medicine and Imaging, Oncology and Artificial Intelligence. According to data from OpenAlex, Minuk Ma has authored 14 papers receiving a total of 235 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Radiology, Nuclear Medicine and Imaging, 8 papers in Oncology and 5 papers in Artificial Intelligence. Recurrent topics in Minuk Ma's work include Radiomics and Machine Learning in Medical Imaging (9 papers), Cancer Immunotherapy and Biomarkers (7 papers) and Multimodal Machine Learning Applications (3 papers). Minuk Ma is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (9 papers), Cancer Immunotherapy and Biomarkers (7 papers) and Multimodal Machine Learning Applications (3 papers). Minuk Ma collaborates with scholars based in South Korea, United States and Hong Kong. Minuk Ma's co-authors include Chang D. Yoo, Junyeong Kim, Kyungsu Kim, Sung-Jin Kim, Trung X. Pham, Seonwook Park, Chan‐Young Ock, Soo Ick Cho, Seokhwi Kim and Sangjoon Choi and has published in prestigious journals such as Journal of Clinical Oncology, European Journal of Cancer and Histopathology.

In The Last Decade

Minuk Ma

14 papers receiving 233 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Minuk Ma South Korea 8 114 113 68 65 32 14 235
Ran Gu China 12 122 1.1× 113 1.0× 136 2.0× 52 0.8× 47 1.5× 30 328
Can Koyuncu United States 10 123 1.1× 69 0.6× 106 1.6× 62 1.0× 30 0.9× 21 253
Jesper Molin Sweden 8 242 2.1× 68 0.6× 123 1.8× 40 0.6× 27 0.8× 18 318
Niccolò Marini Switzerland 9 157 1.4× 74 0.7× 102 1.5× 27 0.4× 27 0.8× 20 213
Lídia Tortajada Spain 9 131 1.1× 62 0.5× 120 1.8× 48 0.7× 41 1.3× 14 271
Mason McGough United States 3 151 1.3× 55 0.5× 84 1.2× 38 0.6× 19 0.6× 4 196
Mart van Rijthoven Netherlands 7 231 2.0× 116 1.0× 169 2.5× 76 1.2× 21 0.7× 8 338
Shazia Akbar United Kingdom 8 150 1.3× 104 0.9× 116 1.7× 34 0.5× 18 0.6× 20 269
Haoran Huang China 7 151 1.3× 33 0.3× 44 0.6× 58 0.9× 8 0.3× 11 273
Radhika Sivaramakrishna United States 8 185 1.6× 130 1.2× 188 2.8× 46 0.7× 87 2.7× 14 369

Countries citing papers authored by Minuk Ma

Since Specialization
Citations

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

Fields of papers citing papers by Minuk Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Minuk Ma

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

All Works

14 of 14 papers shown
1.
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
2.
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
3.
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
4.
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
5.
Cho, Soo Youn, Eun Yoon Cho, So‐Woon Kim, et al.. (2023). Artificial intelligence–powered tumor-infiltrating lymphocytes analyzer to reveal distinct immune landscapes in breast cancer by molecular subtype and HER2 score.. Journal of Clinical Oncology. 41(16_suppl). 1049–1049. 1 indexed citations
6.
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
7.
Kim, Young‐Gon, In Hye Song, Sungchul Kim, et al.. (2022). Diagnostic Assessment of Deep Learning Algorithms for Frozen Tissue Section Analysis in Women with Breast Cancer. Cancer Research and Treatment. 55(2). 513–522. 2 indexed citations
8.
9.
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
10.
Cho, Soo Ick, Sangjoon Choi, Jiwon Shin, et al.. (2022). Artificial Intelligence-Powered Whole-Slide Image Analyzer Reveals a Distinctive Distribution of Tumor-Infiltrating Lymphocytes in Neuroendocrine Neoplasms. Diagnostics. 12(10). 2340–2340. 7 indexed citations
11.
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
12.
Kim, Junyeong, Minuk Ma, Trung X. Pham, Kyungsu Kim, & Chang D. Yoo. (2020). Modality Shifting Attention Network for Multi-Modal Video Question Answering. 10103–10112. 55 indexed citations
13.
Kim, Junyeong, Minuk Ma, Kyungsu Kim, Sung-Jin Kim, & Chang D. Yoo. (2019). Progressive Attention Memory Network for Movie Story Question Answering. 8329–8338. 50 indexed citations
14.
Kim, Junyeong, Minuk Ma, Kyungsu Kim, Sung-Jin Kim, & Chang D. Yoo. (2019). Gaining Extra Supervision via Multi-task learning for Multi-Modal Video Question Answering. 1–8. 16 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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