Richard Dybowski
- Artificial Intelligence top 5%
- Molecular Biology
- Epidemiology
- Health Information Management top 5%
- Infectious Diseases
- Co-authors
- Vanya GantPeter WellerDirk HusmeierStephen RobertsOlivier RestifPietro MastroeniAndrew J. GrantDuncan J. Maskell
- Topics
- Salmonella and Campylobacter epidemiology (5 papers)Vibrio bacteria research studies (5 papers)Escherichia coli research studies (5 papers)
- Partner nations
- United KingdomUnited StatesCanada
In The Last Decade
Richard Dybowski
27 papers receiving 715 citations
Peers
Comparison fields: 5 of 155
- Artificial Intelligence 226
- Molecular Biology 123
- Epidemiology 101
- Health Information Management 56
- Infectious Diseases 53
Countries citing papers authored by Richard Dybowski
This map shows the geographic impact of Richard Dybowski'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 Richard Dybowski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Richard Dybowski more than expected).
Fields of papers citing papers by Richard Dybowski
This network shows the impact of papers produced by Richard Dybowski. 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 Richard Dybowski. The network helps show where Richard Dybowski may publish in the future.
Co-authorship network of co-authors of Richard Dybowski
This figure shows the co-authorship network connecting the top 25 collaborators of Richard Dybowski. A scholar is included among the top collaborators of Richard Dybowski 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 Richard Dybowski. Richard Dybowski is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 42 | |
| 2 | 1 | |
| 3 | 7 | |
| 4 | 10 | |
| 5 | 9 | |
| 6 | 27 | |
| 7 | 8 | |
| 8 | Introduction to the special issue on the fusion of domain knowledge with data for decision support | 12 |
| 9 | 112 | |
| 10 | 10 | |
| 11 | 10 | |
| 12 | 10 | |
| 13 | Visualization of binary string convergence by Sammon mapping | 20 |
| 14 | 171 | |
| 15 | Prediction of Outcome in the Critically Ill Using an Artificial Neural Network Synthesised By a Genetic Algorithm | 1 |
| 16 | 96 | |
| 17 | 3 | |
| 18 | 4 | |
| 19 | 4 | |
| 20 | 1 |
About Richard Dybowski
Richard Dybowski is a scholar working on Endocrinology, Anatomy and Applied Microbiology and Biotechnology, having authored 29 papers that have together received 750 indexed citations. Recurring topics across this work include Salmonella and Campylobacter epidemiology (5 papers), Vibrio bacteria research studies (5 papers) and Escherichia coli research studies (5 papers). The work is most often cited by research in Health Information Management (56 citations), Health Informatics (15 citations) and Endocrinology (41 citations). Richard Dybowski has collaborated with scholars based in United Kingdom, United States and Canada. Frequent co-authors include Vanya Gant, Peter Weller, Dirk Husmeier, Stephen Roberts, Olivier Restif, Pietro Mastroeni, Andrew J. Grant, Duncan J. Maskell, Trevor Collins and James W. Larrick. Their work appears in journals such as The Lancet, PLoS ONE and Antimicrobial Agents and Chemotherapy.
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.