Nai‐Ming Cheng
Impact in
- Otorhinolaryngology top 5%
- Head and Neck Cancer Studies
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- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging Techniques and Applications
- MRI in cancer diagnosis
Papers in
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- Head and Neck Cancer Studies 11
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- Radiomics and Machine Learning in Medical Imaging 11
- Medical Imaging Techniques and Applications 5
- MRI in cancer diagnosis 4
- Co-authors
- Shu‐Hang Ng (10 shared papers)Tzu‐Chen Yen (7 shared papers)Chun‐Ta Liao (9 shared papers)Chien‐Yu Lin (9 shared papers)Hung‐Ming Wang (5 shared papers)Cheng–Lung Hsu (3 shared papers)Din‐Li Tsan (4 shared papers)Sheng-Chieh Chan (5 shared papers)
- Journals
- European Journal of Nuclear Medicine and Molecular Imaging (3 papers)Radiotherapy and Oncology (2 papers)EJNMMI Research (2 papers)Cancers (1 paper)Clinical Cancer Research (1 paper)
- Partner nations
- TaiwanUnited StatesChina
In The Last Decade
Nai‐Ming Cheng
15 papers receiving 225 citations
Peers
Comparison fields: 5 of 33
- Otorhinolaryngology 108
- Radiology, Nuclear Medicine and Imaging 169
- Pulmonary and Respiratory Medicine 72
- Surgery 61
- Microbiology 1
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-authors
The 25 scholars most cited alongside Nai‐Ming Cheng, 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 | 2012 | 43 | |
| 2 | 2021 | 36 | |
| 3 | 2017 | 33 | |
| 4 | 2015 | 19 | |
| 5 | 2008 | 16 | |
| 6 | 2018 | 16 | |
| 7 | 2011 | 12 | |
| 8 | 2019 | 11 | |
| 9 | 2020 | 10 | |
| 10 | 2020 | 9 | |
| 11 | 2022 | 7 | |
| 12 | 2022 | 5 | |
| 13 | 2023 | 5 | |
| 14 | 2023 | 2 | |
| 15 | 2025 | 1 | |
| 16 | 2024 | 0 | |
| 17 | 2024 | 0 | |
| 18 | 2023 | 0 |
About Nai‐Ming Cheng
Nai‐Ming Cheng is a scholar working on Otorhinolaryngology, Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Surgery and Oncology, having authored 18 papers that have together received 225 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (11 papers), Head and Neck Cancer Studies (11 papers), Medical Imaging Techniques and Applications (5 papers), MRI in cancer diagnosis (4 papers), Salivary Gland Tumors Diagnosis and Treatment (4 papers), Lung Cancer Diagnosis and Treatment (3 papers), Ear and Head Tumors (3 papers) and Sarcoma Diagnosis and Treatment (3 papers). The work is most often cited by research in Otorhinolaryngology (108 citations), Radiology, Nuclear Medicine and Imaging (169 citations), Pulmonary and Respiratory Medicine (72 citations), Surgery (61 citations) and Microbiology (1 citation). Nai‐Ming Cheng has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include Shu‐Hang Ng, Tzu‐Chen Yen, Chun‐Ta Liao, Chien‐Yu Lin, Hung‐Ming Wang, Cheng–Lung Hsu, Din‐Li Tsan, Sheng-Chieh Chan, Joseph Tung‐Chieh Chang and Chien-Yu Lin. Their work appears in journals such as European Journal of Nuclear Medicine and Molecular Imaging, Radiotherapy and Oncology, EJNMMI Research, Cancers and Clinical Cancer Research.
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.