Minuk Ma
Impact in
-
- Multimodal Machine Learning Applications
- Human Pose and Action Recognition
- Advanced Image and Video Retrieval Techniques
- Video Analysis and Summarization
- Artificial Intelligence top 10%
- Domain Adaptation and Few-Shot Learning
- AI in cancer detection
Papers in
- Oncology 6
- Cancer Immunotherapy and Biomarkers 5
-
- Domain Adaptation and Few-Shot Learning 3
- AI in cancer detection 2
- Co-authors
- Kyungsu Kim (3 shared papers)Junyeong Kim (3 shared papers)Chang D. Yoo (3 shared papers)Sung-Jin Kim (2 shared papers)Trung X. Pham (1 shared paper)Chan‐Young Ock (10 shared papers)Seonwook Park (8 shared papers)Soo Ick Cho (8 shared papers)
- Journals
- Journal of Clinical Oncology (4 papers)European Journal of Cancer (1 paper)Cancer Research and Treatment (1 paper)npj Breast Cancer (1 paper)Histopathology (1 paper)
- Partner nations
- South KoreaUnited StatesHong Kong
In The Last Decade
Minuk Ma
14 papers receiving 246 citations
Peers
Comparison fields: 5 of 35
- Computer Vision and Pattern Recognition 117
- Artificial Intelligence 111
- Radiology, Nuclear Medicine and Imaging 50
- Oncology 54
- Cancer Research 23
Countries citing papers authored by Minuk Ma
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
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-authors
The 25 scholars most cited alongside Minuk Ma, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 57 | |
| 2 | 2019 | 52 | |
| 3 | 2022 | 44 | |
| 4 | 2023 | 27 | |
| 5 | 2019 | 16 | |
| 6 | 2024 | 13 | |
| 7 | 2022 | 10 | |
| 8 | 2022 | 8 | |
| 9 | 2022 | 7 | |
| 10 | 2023 | 5 | |
| 11 | 2024 | 5 | |
| 12 | 2022 | 2 | |
| 13 | 2023 | 1 | |
| 14 | 2023 | 1 |
About Minuk Ma
Minuk Ma is a scholar working on Oncology, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Computer Vision and Pattern Recognition, having authored 14 papers that have together received 248 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (5 papers), Cancer Immunotherapy and Biomarkers (5 papers), Multimodal Machine Learning Applications (3 papers), Domain Adaptation and Few-Shot Learning (3 papers), Ferroptosis and cancer prognosis (2 papers), AI in cancer detection (2 papers), Human Pose and Action Recognition (2 papers) and Bladder and Urothelial Cancer Treatments (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (117 citations), Artificial Intelligence (111 citations), Radiology, Nuclear Medicine and Imaging (50 citations), Oncology (54 citations) and Cancer Research (23 citations). Minuk Ma has collaborated with scholars based in South Korea, United States and Hong Kong. Frequent co-authors include Kyungsu Kim, Junyeong Kim, Chang D. Yoo, Sung-Jin Kim, Trung X. Pham, Chan‐Young Ock, Seonwook Park, Soo Ick Cho, Sérgio Pereira and Sangjoon Choi. Their work appears in journals such as Journal of Clinical Oncology, European Journal of Cancer, Cancer Research and Treatment, npj Breast Cancer and Histopathology.
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.