Nai-Ming Cheng
- Radiology, Nuclear Medicine and Imaging top 5%
- Pulmonary and Respiratory Medicine
- Otorhinolaryngology top 5%
- Biomedical Engineering
- Surgery
- Co-authors
- Yu-Hua FangTzu‐Chen YenChun-Ta LiaoShu‐Hang NgDin‐Li TsanJoseph Tung‐Chieh ChangHung‐Ming WangChien‐Yu Lin
- Topics
- Radiomics and Machine Learning in Medical Imaging (7 papers)Medical Imaging Techniques and Applications (4 papers)Head and Neck Cancer Studies (4 papers)
- Cited by
- OtorhinolaryngologyRadiology, Nuclear Medicine and ImagingPulmonary and Respiratory Medicine
- Journals
- PLoS ONEJournal of Nuclear MedicineEuropean Journal of Nuclear Medicine and Molecular Imaging
- Partner nations
- TaiwanUnited States
In The Last Decade
Nai-Ming Cheng
10 papers receiving 376 citations
Peers
Comparison fields: 5 of 30
- Radiology, Nuclear Medicine and Imaging 329
- Pulmonary and Respiratory Medicine 124
- Otorhinolaryngology 108
- Biomedical Engineering 71
- Surgery 68
Countries citing papers authored by Nai-Ming Cheng
This map shows the geographic impact of Nai-Ming Cheng'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 Nai-Ming Cheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nai-Ming Cheng more than expected).
Fields of papers citing papers by Nai-Ming Cheng
This network shows the impact of papers produced by Nai-Ming Cheng. 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 Nai-Ming Cheng. The network helps show where Nai-Ming Cheng may publish in the future.
Co-authorship network of co-authors of Nai-Ming Cheng
This figure shows the co-authorship network connecting the top 25 collaborators of Nai-Ming Cheng. A scholar is included among the top collaborators of Nai-Ming Cheng 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 Nai-Ming Cheng. Nai-Ming Cheng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 28 | |
| 3 | 18 | |
| 4 | 8 | |
| 5 | 27 | |
| 6 | 21 | |
| 7 | 19 | |
| 8 | 103 | |
| 9 | 124 | |
| 10 | 29 |
About Nai-Ming Cheng
Nai-Ming Cheng is a scholar working on Otorhinolaryngology, Radiology, Nuclear Medicine and Imaging and Obstetrics and Gynecology, having authored 10 papers that have together received 378 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (7 papers), Medical Imaging Techniques and Applications (4 papers) and Head and Neck Cancer Studies (4 papers). The work is most often cited by research in Otorhinolaryngology (108 citations), Radiology, Nuclear Medicine and Imaging (329 citations) and Pulmonary and Respiratory Medicine (124 citations). Nai-Ming Cheng has collaborated with scholars based in Taiwan and United States. Frequent co-authors include Yu-Hua Fang, Tzu‐Chen Yen, Chun-Ta Liao, Shu‐Hang Ng, Din‐Li Tsan, Joseph Tung‐Chieh Chang, Hung‐Ming Wang, Chien‐Yu Lin, Ching‐Han Hsu and Chung‐Guei Huang. Their work appears in journals such as PLoS ONE, Journal of Nuclear Medicine and European Journal of Nuclear Medicine and Molecular Imaging.
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.