Kevin M. Carter
About
In The Last Decade
Kevin M. Carter
22 papers receiving 222 citations
Peers
Comparison fields: 5 of 60
- Computer Networks and Communications 97
- Artificial Intelligence 95
- Information Systems 64
- Signal Processing 56
- Molecular Biology 45
Countries citing papers authored by Kevin M. Carter
This map shows the geographic impact of Kevin M. Carter'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 Kevin M. Carter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kevin M. Carter more than expected).
Fields of papers citing papers by Kevin M. Carter
This network shows the impact of papers produced by Kevin M. Carter. 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 Kevin M. Carter. The network helps show where Kevin M. Carter may publish in the future.
Co-authorship network of co-authors of Kevin M. Carter
This figure shows the co-authorship network connecting the top 25 collaborators of Kevin M. Carter. A scholar is included among the top collaborators of Kevin M. Carter 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 Kevin M. Carter. Kevin M. Carter is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Toward Finding Malicious Cyber Discussions in Social Media. | 3 |
| 2 | 2 | |
| 3 | 8 | |
| 4 | Characterizing Latent User Interests on Enterprise Networks. | 1 |
| 5 | 22 | |
| 6 | 13 | |
| 7 | 41 | |
| 8 | An Expectation Maximization Approach to Detecting Compromised Remote Access Accounts | 1 |
| 9 | 7 | |
| 10 | 32 | |
| 11 | 5 | |
| 12 | 2 | |
| 13 | 13 | |
| 14 | 9 | |
| 15 | 1 | |
| 16 | Analysis of clinical flow cytometric immunophenotyping data by clustering on statistical manifolds: Treating flow cytometry data as high-dimensional objects How to cite this article: Finn WG, Carter KM, Raich R, Stoolman LM, Hero AO. Analysis of clinical flow cytometric immunophenotyping data by clustering on statistical manifolds: Treating flow cytometry data as high-dimensional objects. Cytometry Part B 2009; 76B: 1–7. | 1 |
| 17 | 6 | |
| 18 | 14 | |
| 19 | 34 | |
| 20 | 10 |
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.