Meng-Hsiun Tsai
- Computer Vision and Pattern Recognition top 5%
- Pollution top 10%
- Health, Toxicology and Mutagenesis top 10%
- Pulmonary and Respiratory Medicine
- Artificial Intelligence
- Co-authors
- Oscar C. PancorboYung‐Kuan ChanChi-Ying HsiehDavid RyanYung-Fu ChenMohammad Mehedi HassanYen‐Ping ChuGiancarlo Fortino
- Topics
- AI in cancer detection (4 papers)Gene expression and cancer classification (4 papers)Digital Imaging for Blood Diseases (3 papers)
- Partner nations
- TaiwanUnited StatesSaudi Arabia
In The Last Decade
Meng-Hsiun Tsai
23 papers receiving 507 citations
Peers
Comparison fields: 5 of 126
- Computer Vision and Pattern Recognition 177
- Pollution 76
- Health, Toxicology and Mutagenesis 76
- Pulmonary and Respiratory Medicine 67
- Artificial Intelligence 63
Countries citing papers authored by Meng-Hsiun Tsai
This map shows the geographic impact of Meng-Hsiun Tsai'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 Meng-Hsiun Tsai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Meng-Hsiun Tsai more than expected).
Fields of papers citing papers by Meng-Hsiun Tsai
This network shows the impact of papers produced by Meng-Hsiun Tsai. 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 Meng-Hsiun Tsai. The network helps show where Meng-Hsiun Tsai may publish in the future.
Co-authorship network of co-authors of Meng-Hsiun Tsai
This figure shows the co-authorship network connecting the top 25 collaborators of Meng-Hsiun Tsai. A scholar is included among the top collaborators of Meng-Hsiun Tsai 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 Meng-Hsiun Tsai. Meng-Hsiun Tsai 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 | 11 | |
| 3 | 1 | |
| 4 | 5 | |
| 5 | 106 | |
| 6 | Application of Machine Learning in Analysis of Transcriptomic Data Derived from Next Generation Sequencing | 2 |
| 7 | 1 | |
| 8 | 32 | |
| 9 | 14 | |
| 10 | Application of Back-propagation Neural Network to Formulate Exercise Prescription for Taiwanese College Students | 1 |
| 11 | 66 | |
| 12 | 15 | |
| 13 | 1 | |
| 14 | 14 | |
| 15 | 6 | |
| 16 | STATISTICAL AND SVM-BASED ONCOGENE DETECTION OF HUMAN CDNA EXPRESSIONS FOR OVARIAN CARCINOMA | 3 |
| 17 | 6 | |
| 18 | 76 | |
| 19 | 1 | |
| 20 | 155 |
About Meng-Hsiun Tsai
Meng-Hsiun Tsai is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Physical Therapy, Sports Therapy and Rehabilitation, having authored 24 papers that have together received 544 indexed citations. Recurring topics across this work include AI in cancer detection (4 papers), Gene expression and cancer classification (4 papers) and Digital Imaging for Blood Diseases (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (177 citations), Pollution (76 citations) and Health, Toxicology and Mutagenesis (76 citations). Meng-Hsiun Tsai has collaborated with scholars based in Taiwan, United States and Saudi Arabia. Frequent co-authors include Oscar C. Pancorbo, Yung‐Kuan Chan, Chi-Ying Hsieh, David Ryan, Yung-Fu Chen, Mohammad Mehedi Hassan, Yen‐Ping Chu, Giancarlo Fortino, SK Hafizul Islam and Jimmy Ming‐Tai Wu. Their work appears in journals such as The Science of The Total Environment, BMC Bioinformatics and Information Sciences.
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.