Ian H. Jarman
- Orthopedics and Sports Medicine top 5%
- Artificial Intelligence top 10%
- Epidemiology
- Molecular Biology
- General Health Professions
- Co-authors
- Paulo LisböaTerence A. EtchellsBarry DrustMatthew WestonWarren GregsonNaomi DatsonJosé D. Martín‐GuerreroMark A Bellis
- Topics
- Advanced Clustering Algorithms Research (5 papers)Gene expression and cancer classification (4 papers)Sports Performance and Training (3 papers)
- Partner nations
- United KingdomSpainItaly
In The Last Decade
Ian H. Jarman
44 papers receiving 736 citations
Peers
Comparison fields: 5 of 151
- Orthopedics and Sports Medicine 144
- Artificial Intelligence 108
- Epidemiology 93
- Molecular Biology 79
- General Health Professions 71
Countries citing papers authored by Ian H. Jarman
This map shows the geographic impact of Ian H. Jarman'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 Ian H. Jarman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ian H. Jarman more than expected).
Fields of papers citing papers by Ian H. Jarman
This network shows the impact of papers produced by Ian H. Jarman. 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 Ian H. Jarman. The network helps show where Ian H. Jarman may publish in the future.
Co-authorship network of co-authors of Ian H. Jarman
This figure shows the co-authorship network connecting the top 25 collaborators of Ian H. Jarman. A scholar is included among the top collaborators of Ian H. Jarman 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 Ian H. Jarman. Ian H. Jarman 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 | 2 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 11 | |
| 6 | 5 | |
| 7 | 2 | |
| 8 | 2 | |
| 9 | 8 | |
| 10 | Performance assessment of quantum clustering in non-spherical data distributions. | 2 |
| 11 | 70 | |
| 12 | 29 | |
| 13 | Constructing similarity networks using the Fisher information metric. | 2 |
| 14 | The role of Fisher information in primary data space for neighbourhood mapping | 5 |
| 15 | 14 | |
| 16 | 17 | |
| 17 | 22 | |
| 18 | 27 | |
| 19 | 31 | |
| 20 | 11 |
About Ian H. Jarman
Ian H. Jarman is a scholar working on Artificial Intelligence, Applied Microbiology and Biotechnology and Statistics and Probability, having authored 48 papers that have together received 765 indexed citations. Recurring topics across this work include Advanced Clustering Algorithms Research (5 papers), Gene expression and cancer classification (4 papers) and Sports Performance and Training (3 papers). The work is most often cited by research in Orthopedics and Sports Medicine (144 citations), Health (58 citations) and Applied Microbiology and Biotechnology (9 citations). Ian H. Jarman has collaborated with scholars based in United Kingdom, Spain and Italy. Frequent co-authors include Paulo Lisböa, Terence A. Etchells, Barry Drust, Matthew Weston, Warren Gregson, Naomi Datson, José D. Martín‐Guerrero, Mark A Bellis, Richard Lowsby and Patrick Née. Their work appears in journals such as PLoS ONE, The British Journal of Psychiatry and BMC Bioinformatics.
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.