Shih‐Chung B. Lo
- Artificial Intelligence top 2%
- Radiology, Nuclear Medicine and Imaging top 5%
- Computer Vision and Pattern Recognition top 5%
- Pulmonary and Respiratory Medicine top 10%
- Biomedical Engineering
- Co-authors
- Matthew T. FreedmanSeong K. MunHeang‐Ping ChanHuai LiJyh-Shyan LinKwok L. LamBerkman SahinerMark A. Helvie
- Topics
- AI in cancer detection (32 papers)Radiomics and Machine Learning in Medical Imaging (24 papers)Digital Radiography and Breast Imaging (15 papers)
- Partner nations
- United StatesSpainUnited Kingdom
In The Last Decade
Shih‐Chung B. Lo
68 papers receiving 925 citations
Peers
Comparison fields: 5 of 114
- Artificial Intelligence 511
- Radiology, Nuclear Medicine and Imaging 497
- Computer Vision and Pattern Recognition 309
- Pulmonary and Respiratory Medicine 244
- Biomedical Engineering 135
Countries citing papers authored by Shih‐Chung B. Lo
This map shows the geographic impact of Shih‐Chung B. Lo'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 Shih‐Chung B. Lo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shih‐Chung B. Lo more than expected).
Fields of papers citing papers by Shih‐Chung B. Lo
This network shows the impact of papers produced by Shih‐Chung B. Lo. 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 Shih‐Chung B. Lo. The network helps show where Shih‐Chung B. Lo may publish in the future.
Co-authorship network of co-authors of Shih‐Chung B. Lo
This figure shows the co-authorship network connecting the top 25 collaborators of Shih‐Chung B. Lo. A scholar is included among the top collaborators of Shih‐Chung B. Lo 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 Shih‐Chung B. Lo. Shih‐Chung B. Lo 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 | 55 | |
| 3 | 31 | |
| 4 | 16 | |
| 5 | 2 | |
| 6 | 0 | |
| 7 | 9 | |
| 8 | 1 | |
| 9 | 13 | |
| 10 | 61 | |
| 11 | 7 | |
| 12 | 1 | |
| 13 | 26 | |
| 14 | 159 | |
| 15 | 22 | |
| 16 | 7 | |
| 17 | 1 | |
| 18 | 2 | |
| 19 | 4 | |
| 20 | 13 |
About Shih‐Chung B. Lo
Shih‐Chung B. Lo is a scholar working on Radiology, Nuclear Medicine and Imaging, Health Informatics and Computer Vision and Pattern Recognition, having authored 73 papers that have together received 961 indexed citations. Recurring topics across this work include AI in cancer detection (32 papers), Radiomics and Machine Learning in Medical Imaging (24 papers) and Digital Radiography and Breast Imaging (15 papers). The work is most often cited by research in Health Informatics (56 citations), Radiology, Nuclear Medicine and Imaging (497 citations) and Artificial Intelligence (511 citations). Shih‐Chung B. Lo has collaborated with scholars based in United States, Spain and United Kingdom. Frequent co-authors include Matthew T. Freedman, Seong K. Mun, Heang‐Ping Chan, Huai Li, Jyh-Shyan Lin, Kwok L. Lam, Berkman Sahiner, Mark A. Helvie, Yue J. Wang and Lisa M. Kinnard. Their work appears in journals such as IEEE Transactions on Medical Imaging, American Journal of Roentgenology and Medical Physics.
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.