Myeongchan Kim
- Radiology, Nuclear Medicine and Imaging top 5%
- Artificial Intelligence top 10%
- Health Informatics top 1%
- Pulmonary and Respiratory Medicine
- Epidemiology
- Co-authors
- Synho DoSehyo YuneHyunkwang LeeShahein TajmirMohammad MansouriRamón GonzálezStuart R. PomerantzJavier M. Romero
- Topics
- Radiomics and Machine Learning in Medical Imaging (3 papers)Influenza Virus Research Studies (3 papers)Machine Learning in Healthcare (3 papers)
- Journals
- SHILAP Revista de lepidopterologíaScientific ReportsRadiology
- Partner nations
- South KoreaUnited StatesGermany
In The Last Decade
Myeongchan Kim
10 papers receiving 574 citations
Hit Papers
Peers
Comparison fields: 5 of 101
- Radiology, Nuclear Medicine and Imaging 299
- Artificial Intelligence 176
- Health Informatics 127
- Pulmonary and Respiratory Medicine 116
- Epidemiology 99
Countries citing papers authored by Myeongchan Kim
This map shows the geographic impact of Myeongchan 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 Myeongchan Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Myeongchan Kim more than expected).
Fields of papers citing papers by Myeongchan Kim
This network shows the impact of papers produced by Myeongchan 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 Myeongchan Kim. The network helps show where Myeongchan Kim may publish in the future.
Co-authorship network of co-authors of Myeongchan Kim
This figure shows the co-authorship network connecting the top 25 collaborators of Myeongchan Kim. A scholar is included among the top collaborators of Myeongchan 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 Myeongchan Kim. Myeongchan Kim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 3 | |
| 4 | 0 | |
| 5 | 9 | |
| 6 | 13 | |
| 7 | 11 | |
| 8 | 33 | |
| 9 | 169 | |
| 10 | 0 | |
| 11 | 9 | |
| 12 | 30 | |
| 13 | An explainable deep-learning algorithm for the detection of acute intracranial haemorrhage from small datasetsbreakdown → | 309 |
About Myeongchan Kim
Myeongchan Kim is a scholar working on Health Informatics, Critical Care and Intensive Care Medicine and Radiology, Nuclear Medicine and Imaging, having authored 13 papers that have together received 587 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (3 papers), Influenza Virus Research Studies (3 papers) and Machine Learning in Healthcare (3 papers). The work is most often cited by research in Health Informatics (127 citations), Radiology, Nuclear Medicine and Imaging (299 citations) and Neurology (54 citations). Myeongchan Kim has collaborated with scholars based in South Korea, United States and Germany. Frequent co-authors include Synho Do, Sehyo Yune, Hyunkwang Lee, Shahein Tajmir, Mohammad Mansouri, Ramón González, Stuart R. Pomerantz, Javier M. Romero, Shahmir Kamalian and Michael H. Lev. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and Radiology.
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.