John Maddison
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
Papers in ⓘ
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- Artificial Intelligence in Healthcare and Education 2
- Co-authors
- Inger Nina Farstad (1 shared paper)Sepp de Raedt (1 shared paper)Ian Tomlinson (1 shared paper)David N. Church (1 shared paper)Rachel Kerr (1 shared paper)John Arne Nesheim (2 shared papers)Hanne A. Askautrud (1 shared paper)Manohar Pradhan (1 shared paper)
- Journals
- Journal of Clinical Pathology (2 papers)Expert Review of Molecular Diagnostics (2 papers)Progress in Retinal and Eye Research (1 paper)Histopathology (1 paper)ANZ Journal of Surgery (1 paper)
- Partner nations
- United KingdomAustraliaUnited States
In The Last Decade
John Maddison
16 papers receiving 535 citations
Hit Papers
Peers
Comparison fields: 5 of 89
- Health Informatics 37
- Radiology, Nuclear Medicine and Imaging 295
- Ophthalmology 63
- Oncology 189
- Artificial Intelligence 215
Countries citing papers authored by John Maddison
This map shows the geographic impact of John Maddison'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 John Maddison with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Maddison more than expected).
Fields of papers citing papers by John Maddison
This network shows the impact of papers produced by John Maddison. 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 John Maddison. The network helps show where John Maddison may publish in the future.
Co-authors
The 25 scholars most cited alongside John Maddison, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Deep learning for prediction of colorectal cancer outcome: a discovery and validation study Hit paper breakdown → | 2020 | 393 |
| 2 | 2021 | 40 | |
| 3 | 2020 | 32 | |
| 4 | 2009 | 14 | |
| 5 | 2005 | 13 | |
| 6 | Analysing the 3D Structure of Blood Vessels using Confocal Microscopy | 2002 | 12 |
| 7 | 2014 | 11 | |
| 8 | 2020 | 8 | |
| 9 | 2024 | 6 | |
| 10 | 2024 | 4 | |
| 11 | 2025 | 3 | |
| 12 | 2024 | 2 | |
| 13 | 2024 | 1 | |
| 14 | 2006 | 1 | |
| 15 | 2000 | 1 | |
| 16 | 3-dimensional analysis of vascular structure, function & receptor distribution using confocal laser scanning microscopy | 2000 | 1 |
| 17 | 2024 | 0 | |
| 18 | 2025 | 0 |
About John Maddison
John Maddison is a scholar working on Health Informatics, Family Practice, Health Information Management, Biophysics and Ophthalmology, having authored 18 papers that have together received 542 indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (3 papers), Retinal Diseases and Treatments (3 papers), Cell Image Analysis Techniques (2 papers), Glaucoma and retinal disorders (2 papers), Emergency and Acute Care Studies (2 papers), Artificial Intelligence in Healthcare and Education (2 papers), Electronic Health Records Systems (2 papers) and AI in cancer detection (2 papers). The work is most often cited by research in Health Informatics (37 citations), Radiology, Nuclear Medicine and Imaging (295 citations), Ophthalmology (63 citations), Oncology (189 citations) and Artificial Intelligence (215 citations). John Maddison has collaborated with scholars based in United Kingdom, Australia and United States. Frequent co-authors include Inger Nina Farstad, Sepp de Raedt, Ian Tomlinson, David N. Church, Rachel Kerr, John Arne Nesheim, Hanne A. Askautrud, Manohar Pradhan, Ole-Johan Skrede and Knut Liestøl. Their work appears in journals such as Journal of Clinical Pathology, Expert Review of Molecular Diagnostics, Progress in Retinal and Eye Research, Histopathology and ANZ Journal of Surgery.
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.