Matt Kelly
- Epidemiology top 2%
- Hepatology top 1%
- Molecular Biology
- Genetics top 5%
- Cancer Research top 5%
- Co-authors
- Rajarshi BanerjeeStefan NeubauerChristopher SemsarianMichael PavlidesKatarzyna BlochDavid Robert GrimesMike PartridgeS. S. Moore
- Topics
- Liver Disease Diagnosis and Treatment (42 papers)Genetic and phenotypic traits in livestock (26 papers)Liver Disease and Transplantation (20 papers)
- Partner nations
- United KingdomAustraliaUnited States
In The Last Decade
Matt Kelly
131 papers receiving 3.7k citations
Hit Papers
Peers
Comparison fields: 5 of 163
- Epidemiology 1.3k
- Hepatology 807
- Molecular Biology 686
- Genetics 671
- Cancer Research 429
Countries citing papers authored by Matt Kelly
This map shows the geographic impact of Matt Kelly'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 Matt Kelly with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matt Kelly more than expected).
Fields of papers citing papers by Matt Kelly
This network shows the impact of papers produced by Matt Kelly. 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 Matt Kelly. The network helps show where Matt Kelly may publish in the future.
Co-authorship network of co-authors of Matt Kelly
This figure shows the co-authorship network connecting the top 25 collaborators of Matt Kelly. A scholar is included among the top collaborators of Matt Kelly 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 Matt Kelly. Matt Kelly 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 | Multi-organ impairment and long COVID: a 1-year prospective, longitudinal cohort studybreakdown → | 59 |
| 3 | 3 | |
| 4 | 2 | |
| 5 | 4 | |
| 6 | 135 | |
| 7 | Cross-Sectional, Prospective, Evaluation of the Utility of Multi-Parametric MRI Imaging in Predicting Clinically Meaningful Outcomes in Autoimmune Hepatitis. | 1 |
| 8 | 59 | |
| 9 | 15 | |
| 10 | 60 | |
| 11 | 33 | |
| 12 | 38 | |
| 13 | Determining the number of animals required to accurately determine breed composition using genomic data | 3 |
| 14 | 36 | |
| 15 | Campaign best practice in intravenous therapy. | 2 |
| 16 | 31 | |
| 17 | Comparison of methods for preparing feed intake records for analysis of average daily intake from an automated feed intake monitoring system | 1 |
| 18 | 8 | |
| 19 | 54 | |
| 20 | Residue depletion study of PCDDs and PCDFs in dosed beef cattle | 1 |
About Matt Kelly
Matt Kelly is a scholar working on Hepatology, Cancer Research and Epidemiology, having authored 139 papers that have together received 3.8k indexed citations. Recurring topics across this work include Liver Disease Diagnosis and Treatment (42 papers), Genetic and phenotypic traits in livestock (26 papers) and Liver Disease and Transplantation (20 papers). The work is most often cited by research in Hepatology (807 citations), Epidemiology (1.3k citations) and Cancer Research (429 citations). Matt Kelly has collaborated with scholars based in United Kingdom, Australia and United States. Frequent co-authors include Rajarshi Banerjee, Stefan Neubauer, Christopher Semsarian, Michael Pavlides, Katarzyna Bloch, David Robert Grimes, Mike Partridge, S. S. Moore, Andrea Dennis and Marina R. S. Fortes. Their work appears in journals such as The Lancet, Circulation and Nature Communications.
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.