Ming‐Hung Shih
Impact in
- Signal Processing top 10%
- Advanced Malware Detection Techniques
- Information Systems top 10%
- Blockchain Technology Applications and Security
- User Authentication and Security Systems
Papers in
-
- Blockchain Technology Applications and Security 6
-
- Cryptography and Data Security 3
- Data Stream Mining Techniques 3
- Co-authors
- Dong‐Her Shih (28 shared papers)Binshan Lin (2 shared papers)Hsiu‐Sen Chiang (5 shared papers)C.P. Chang (1 shared paper)P.W. Kao (1 shared paper)Cheng-Fu Yu (1 shared paper)Divesh Srivastava (2 shared papers)David C. Yen (7 shared papers)
- Journals
- Journal of Clinical Medicine (2 papers)IEEE Access (2 papers)Expert Systems with Applications (2 papers)Cartography and Geographic Information Science (1 paper)Industrial Management & Data Systems (1 paper)
- Partner nations
- TaiwanUnited StatesJapan
In The Last Decade
Ming‐Hung Shih
30 papers receiving 328 citations
Peers
Comparison fields: 5 of 101
- Signal Processing 65
- Information Systems 105
- Computer Networks and Communications 62
- Transportation 18
- Artificial Intelligence 72
Countries citing papers authored by Ming‐Hung Shih
This map shows the geographic impact of Ming‐Hung Shih'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 Ming‐Hung Shih with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming‐Hung Shih more than expected).
Fields of papers citing papers by Ming‐Hung Shih
This network shows the impact of papers produced by Ming‐Hung Shih. 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 Ming‐Hung Shih. The network helps show where Ming‐Hung Shih may publish in the future.
Co-authors
The 19 scholars most cited alongside Ming‐Hung Shih, 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 | 2001 | 67 | |
| 2 | 2008 | 55 | |
| 3 | 2020 | 53 | |
| 4 | 2014 | 24 | |
| 5 | 2022 | 21 | |
| 6 | 2021 | 16 | |
| 7 | 2015 | 15 | |
| 8 | 2015 | 15 | |
| 9 | 2011 | 14 | |
| 10 | 2022 | 14 | |
| 11 | 2019 | 10 | |
| 12 | 2022 | 10 | |
| 13 | 2011 | 7 | |
| 14 | 2024 | 3 | |
| 15 | 2023 | 3 | |
| 16 | 2021 | 3 | |
| 17 | 2022 | 3 | |
| 18 | 2017 | 3 | |
| 19 | 2022 | 2 | |
| 20 | 2024 | 2 |
About Ming‐Hung Shih
Ming‐Hung Shih is a scholar working on Information Systems, Artificial Intelligence, Signal Processing, Computer Networks and Communications and Cardiology and Cardiovascular Medicine, having authored 33 papers that have together received 355 indexed citations. Recurring topics across this work include Blockchain Technology Applications and Security (6 papers), Data Management and Algorithms (4 papers), EEG and Brain-Computer Interfaces (4 papers), Cryptography and Data Security (3 papers), ECG Monitoring and Analysis (3 papers), Data Stream Mining Techniques (3 papers), COVID-19 epidemiological studies (3 papers) and Data-Driven Disease Surveillance (2 papers). The work is most often cited by research in Signal Processing (65 citations), Information Systems (105 citations), Computer Networks and Communications (62 citations), Transportation (18 citations) and Artificial Intelligence (72 citations). Ming‐Hung Shih has collaborated with scholars based in Taiwan, United States and Japan. Frequent co-authors include Dong‐Her Shih, Binshan Lin, Hsiu‐Sen Chiang, C.P. Chang, P.W. Kao, Cheng-Fu Yu, Divesh Srivastava, David C. Yen, Trong Duc Nguyen and Srikanta Tirthapura. Their work appears in journals such as Journal of Clinical Medicine, IEEE Access, Expert Systems with Applications, Cartography and Geographic Information Science and Industrial Management & Data Systems.
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.