Terence A. Etchells
- Artificial Intelligence top 10%
- Molecular Biology
- Biomedical Engineering
- Information Systems
- Health Information Management top 10%
- Co-authors
- Paulo LisböaIan H. JarmanFederico AmbrogiElia BiganzoliPatrizia BoracchiDavide BacciuMin Hane AungDaniel Garwicz
- Topics
- Statistical Methods and Inference (4 papers)Neural Networks and Applications (4 papers)Bayesian Modeling and Causal Inference (3 papers)
- Partner nations
- United KingdomItalySpain
In The Last Decade
Terence A. Etchells
22 papers receiving 309 citations
Peers
Comparison fields: 5 of 101
- Artificial Intelligence 139
- Molecular Biology 68
- Biomedical Engineering 32
- Information Systems 25
- Health Information Management 23
Countries citing papers authored by Terence A. Etchells
This map shows the geographic impact of Terence A. Etchells'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 Terence A. Etchells with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Terence A. Etchells more than expected).
Fields of papers citing papers by Terence A. Etchells
This network shows the impact of papers produced by Terence A. Etchells. 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 Terence A. Etchells. The network helps show where Terence A. Etchells may publish in the future.
Co-authorship network of co-authors of Terence A. Etchells
This figure shows the co-authorship network connecting the top 25 collaborators of Terence A. Etchells. A scholar is included among the top collaborators of Terence A. Etchells 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 Terence A. Etchells. Terence A. Etchells is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 26 | |
| 3 | 31 | |
| 4 | 13 | |
| 5 | 1 | |
| 6 | 45 | |
| 7 | 5 | |
| 8 | 27 | |
| 9 | 31 | |
| 10 | 7 | |
| 11 | 1 | |
| 12 | 11 | |
| 13 | 14 | |
| 14 | 3 | |
| 15 | 2 | |
| 16 | 1 | |
| 17 | Learning what is important: feature selection and rule extraction in a virtual course | 20 |
| 18 | 6 | |
| 19 | 61 | |
| 20 | 4 |
About Terence A. Etchells
Terence A. Etchells is a scholar working on Statistics and Probability, Artificial Intelligence and Computational Theory and Mathematics, having authored 23 papers that have together received 325 indexed citations. Recurring topics across this work include Statistical Methods and Inference (4 papers), Neural Networks and Applications (4 papers) and Bayesian Modeling and Causal Inference (3 papers). The work is most often cited by research in Health Informatics (12 citations), Health Information Management (23 citations) and Artificial Intelligence (139 citations). Terence A. Etchells has collaborated with scholars based in United Kingdom, Italy and Spain. Frequent co-authors include Paulo Lisböa, Ian H. Jarman, Federico Ambrogi, Elia Biganzoli, Patrizia Boracchi, Davide Bacciu, Min Hane Aung, Daniel Garwicz, Thorsteinn Rögnvaldsson and Niels Jensby Nedergaard. Their work appears in journals such as BMC Bioinformatics, Neurocomputing 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.