S.-C.B. Lo
Impact in
- Microbiology top 1%
- Microbial infections and disease research
- Reproductive tract infections research
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- Advanced Data Compression Techniques
- Image Retrieval and Classification Techniques
- Image and Signal Denoising Methods
Papers in
-
- Advanced Data Compression Techniques 6
- Image and Signal Denoising Methods 5
- Image Retrieval and Classification Techniques 4
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- AI in cancer detection 8
- Neural Networks and Applications 3
- Co-authors
- Matthew T. Freedman (12 shared papers)Seong K. Mun (8 shared papers)Jyh-Shyan Lin (3 shared papers)K.J. Ray Liu (1 shared paper)Douglas J. Wear (3 shared papers)S.L. Lou (1 shared paper)H. K. Huang (2 shared papers)J W Shih (1 shared paper)
- Journals
- IEEE Transactions on Medical Imaging (8 papers)Radiology (2 papers)Clinical Infectious Diseases (1 paper)JNCI Journal of the National Cancer Institute (1 paper)Gene (1 paper)
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
S.-C.B. Lo
31 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 130
- Microbiology 370
- Computer Vision and Pattern Recognition 385
- Radiology, Nuclear Medicine and Imaging 375
- Artificial Intelligence 470
- Parasitology 59
Countries citing papers authored by S.-C.B. Lo
This map shows the geographic impact of S.-C.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 S.-C.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 S.-C.B. Lo more than expected).
Fields of papers citing papers by S.-C.B. Lo
This network shows the impact of papers produced by S.-C.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 S.-C.B. Lo. The network helps show where S.-C.B. Lo may publish in the future.
Co-authors
The 25 scholars most cited alongside S.-C.B. Lo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1995 | 243 | |
| 2 | 1995 | 140 | |
| 3 | 1997 | 137 | |
| 4 | 2001 | 104 | |
| 5 | 1989 | 95 | |
| 6 | 2001 | 78 | |
| 7 | 2005 | 67 | |
| 8 | 1996 | 61 | |
| 9 | 1992 | 55 | |
| 10 | 1998 | 50 | |
| 11 | 2001 | 48 | |
| 12 | 2003 | 45 | |
| 13 | 1994 | 42 | |
| 14 | 1986 | 40 | |
| 15 | 1985 | 38 | |
| 16 | 1990 | 33 | |
| 17 | 1990 | 30 | |
| 18 | 1988 | 29 | |
| 19 | 2006 | 21 | |
| 20 | 1993 | 19 |
About S.-C.B. Lo
S.-C.B. Lo is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Microbiology, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine, having authored 33 papers that have together received 1.4k indexed citations. Recurring topics across this work include AI in cancer detection (8 papers), Microbial infections and disease research (7 papers), Advanced Data Compression Techniques (6 papers), Image and Signal Denoising Methods (5 papers), Image Retrieval and Classification Techniques (4 papers), COVID-19 diagnosis using AI (3 papers), Neural Networks and Applications (3 papers) and Bacteriophages and microbial interactions (3 papers). The work is most often cited by research in Microbiology (370 citations), Computer Vision and Pattern Recognition (385 citations), Radiology, Nuclear Medicine and Imaging (375 citations), Artificial Intelligence (470 citations) and Parasitology (59 citations). S.-C.B. Lo has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Matthew T. Freedman, Seong K. Mun, Jyh-Shyan Lin, K.J. Ray Liu, Douglas J. Wear, S.L. Lou, H. K. Huang, J W Shih, Shien Tsai and Hua Li. Their work appears in journals such as IEEE Transactions on Medical Imaging, Radiology, Clinical Infectious Diseases, JNCI Journal of the National Cancer Institute and Gene.
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.