Joshua Hatherley
- Health Informatics top 0.5%
- Safety Research top 5%
- Artificial Intelligence top 10%
- Public Health, Environmental and Occupational Health
- Cognitive Neuroscience
- Co-authors
- Robert SparrowMark HowardJohn McMillanJulian KoplinDaniel RodgerPeter V. TreitBrian D. EarpJulian Savulescu
- Topics
- Artificial Intelligence in Healthcare and Education (11 papers)Explainable Artificial Intelligence (XAI) (6 papers)Machine Learning in Healthcare (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaJournal of the American Medical Informatics AssociationNature Machine Intelligence
- Partner nations
- AustraliaDenmarkUnited Kingdom
In The Last Decade
Joshua Hatherley
12 papers receiving 309 citations
Peers
Comparison fields: 5 of 77
- Health Informatics 179
- Safety Research 107
- Artificial Intelligence 102
- Public Health, Environmental and Occupational Health 75
- Cognitive Neuroscience 43
Countries citing papers authored by Joshua Hatherley
This map shows the geographic impact of Joshua Hatherley'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 Joshua Hatherley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joshua Hatherley more than expected).
Fields of papers citing papers by Joshua Hatherley
This network shows the impact of papers produced by Joshua Hatherley. 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 Joshua Hatherley. The network helps show where Joshua Hatherley may publish in the future.
Co-authorship network of co-authors of Joshua Hatherley
This figure shows the co-authorship network connecting the top 25 collaborators of Joshua Hatherley. A scholar is included among the top collaborators of Joshua Hatherley 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 Joshua Hatherley. Joshua Hatherley 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 | 0 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 8 | |
| 7 | 57 | |
| 8 | 16 | |
| 9 | 23 | |
| 10 | 11 | |
| 11 | 132 | |
| 12 | 30 | |
| 13 | 27 | |
| 14 | 10 |
About Joshua Hatherley
Joshua Hatherley is a scholar working on Health Informatics, Family Practice and Safety Research, having authored 14 papers that have together received 318 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (11 papers), Explainable Artificial Intelligence (XAI) (6 papers) and Machine Learning in Healthcare (4 papers). The work is most often cited by research in Health Informatics (179 citations), Safety Research (107 citations) and Family Practice (9 citations). Joshua Hatherley has collaborated with scholars based in Australia, Denmark and United Kingdom. Frequent co-authors include Robert Sparrow, Mark Howard, John McMillan, Julian Koplin, Daniel Rodger, Peter V. Treit, Brian D. Earp, Julian Savulescu, Sven Nyholm and Sebastian Porsdam Mann. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of the American Medical Informatics Association and Nature Machine Intelligence.
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.