Jyh-Shyan Lin
- Radiology, Nuclear Medicine and Imaging top 5%
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Pulmonary and Respiratory Medicine
- Biomedical Engineering
- Co-authors
- Seong K. MunMatthew T. FreedmanS.-C.B. LoShih‐Chung B. LoS.L. LouHuai LiHeang‐Ping ChanPao-Ta Yu
- Topics
- AI in cancer detection (8 papers)COVID-19 diagnosis using AI (8 papers)Radiomics and Machine Learning in Medical Imaging (7 papers)
- Cited by
- Radiology, Nuclear Medicine and ImagingHealth InformaticsComputer Vision and Pattern Recognition
- Journals
- SHILAP Revista de lepidopterologíaIEEE Transactions on Medical ImagingNeural Networks
- Partner nations
- United StatesTaiwan
In The Last Decade
Jyh-Shyan Lin
24 papers receiving 771 citations
Peers
Comparison fields: 5 of 98
- Radiology, Nuclear Medicine and Imaging 380
- Artificial Intelligence 374
- Computer Vision and Pattern Recognition 297
- Pulmonary and Respiratory Medicine 193
- Biomedical Engineering 76
Countries citing papers authored by Jyh-Shyan Lin
This map shows the geographic impact of Jyh-Shyan Lin'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 Jyh-Shyan Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jyh-Shyan Lin more than expected).
Fields of papers citing papers by Jyh-Shyan Lin
This network shows the impact of papers produced by Jyh-Shyan Lin. 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 Jyh-Shyan Lin. The network helps show where Jyh-Shyan Lin may publish in the future.
Co-authorship network of co-authors of Jyh-Shyan Lin
This figure shows the co-authorship network connecting the top 25 collaborators of Jyh-Shyan Lin. A scholar is included among the top collaborators of Jyh-Shyan Lin 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 Jyh-Shyan Lin. Jyh-Shyan Lin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | A hybrid time series model based on AR-EMD and volatility for medical data forecasting: A case study in the emergency department | 1 |
| 3 | Cloud Data Storage for Group Collaborations | 1 |
| 4 | 3 | |
| 5 | 3 | |
| 6 | 111 | |
| 7 | Short communication Digital watermarking based on neural networks for color images | 1 |
| 8 | 12 | |
| 9 | 13 | |
| 10 | 61 | |
| 11 | 1 | |
| 12 | 243 | |
| 13 | 232 | |
| 14 | 1 | |
| 15 | 14 | |
| 16 | 5 | |
| 17 | 4 | |
| 18 | 29 | |
| 19 | 67 | |
| 20 | 2 |
About Jyh-Shyan Lin
Jyh-Shyan Lin is a scholar working on Radiology, Nuclear Medicine and Imaging, General Dentistry and Neurology, having authored 25 papers that have together received 823 indexed citations. Recurring topics across this work include AI in cancer detection (8 papers), COVID-19 diagnosis using AI (8 papers) and Radiomics and Machine Learning in Medical Imaging (7 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (380 citations), Health Informatics (20 citations) and Computer Vision and Pattern Recognition (297 citations). Jyh-Shyan Lin has collaborated with scholars based in United States and Taiwan. Frequent co-authors include Seong K. Mun, Matthew T. Freedman, S.-C.B. Lo, Shih‐Chung B. Lo, S.L. Lou, Huai Li, Heang‐Ping Chan, Pao-Ta Yu, Hung-Hsu Tsai and Akira Hasegawa. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Medical Imaging and Neural Networks.
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.