Ching‐Wei Wang
- Artificial Intelligence top 2%
- Oral Surgery top 1%
- Radiology, Nuclear Medicine and Imaging top 5%
- Computer Vision and Pattern Recognition top 5%
- Biomedical Engineering top 10%
- Co-authors
- Yu‐Ching LeeTai‐Kuang ChaoYi‐Jia LinClaudia LindnerT.F. CootesAndrew HunterSheng‐Wei ChangBulat Ibragimov
- Topics
- AI in cancer detection (26 papers)Cell Image Analysis Techniques (15 papers)Radiomics and Machine Learning in Medical Imaging (12 papers)
- Journals
- SHILAP Revista de lepidopterologíaBioinformaticsPLoS ONE
- Partner nations
- TaiwanUnited KingdomCanada
In The Last Decade
Ching‐Wei Wang
77 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 136
- Artificial Intelligence 567
- Oral Surgery 452
- Radiology, Nuclear Medicine and Imaging 402
- Computer Vision and Pattern Recognition 333
- Biomedical Engineering 326
Countries citing papers authored by Ching‐Wei Wang
This map shows the geographic impact of Ching‐Wei Wang'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 Ching‐Wei Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ching‐Wei Wang more than expected).
Fields of papers citing papers by Ching‐Wei Wang
This network shows the impact of papers produced by Ching‐Wei Wang. 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 Ching‐Wei Wang. The network helps show where Ching‐Wei Wang may publish in the future.
Co-authorship network of co-authors of Ching‐Wei Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Ching‐Wei Wang. A scholar is included among the top collaborators of Ching‐Wei Wang 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 Ching‐Wei Wang. Ching‐Wei Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 3 | |
| 3 | 6 | |
| 4 | 14 | |
| 5 | 10 | |
| 6 | 17 | |
| 7 | 22 | |
| 8 | 36 | |
| 9 | 17 | |
| 10 | 1 | |
| 11 | 31 | |
| 12 | 6 | |
| 13 | 3 | |
| 14 | 7 | |
| 15 | 34 | |
| 16 | 34 | |
| 17 | 15 | |
| 18 | Locating the Upper Body of Covered Humans in application to Diagnosis of Obstructive Sleep Apnea | 8 |
| 19 | Artificial intelligent vision analysis in obstructive sleep apnoea (OSA) | 1 |
| 20 | 14 |
About Ching‐Wei Wang
Ching‐Wei Wang is a scholar working on Biophysics, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 82 papers that have together received 1.8k indexed citations. Recurring topics across this work include AI in cancer detection (26 papers), Cell Image Analysis Techniques (15 papers) and Radiomics and Machine Learning in Medical Imaging (12 papers). The work is most often cited by research in Oral Surgery (452 citations), Health Informatics (71 citations) and Orthodontics (188 citations). Ching‐Wei Wang has collaborated with scholars based in Taiwan, United Kingdom and Canada. Frequent co-authors include Yu‐Ching Lee, Tai‐Kuang Chao, Yi‐Jia Lin, Claudia Lindner, T.F. Cootes, Andrew Hunter, Sheng‐Wei Chang, Bulat Ibragimov, Chung-Hsing Li and Tomaž Vrtovec. Their work appears in journals such as SHILAP Revista de lepidopterología, Bioinformatics and PLoS ONE.
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.