Matthew Field
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging Techniques and Applications
Papers in
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- AI in cancer detection 7
- Anomaly Detection Techniques and Applications 5
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- Lung Cancer Diagnosis and Treatment 10
- Co-authors
- David Stirling (17 shared papers)Lois Holloway (22 shared papers)Fazel Naghdy (10 shared papers)Zengxi Pan (8 shared papers)Montserrat Ros (8 shared papers)Martin Carolan (10 shared papers)Michael Jameson (2 shared papers)Shalini Vinod (11 shared papers)
- Journals
- Cancers (2 papers)Journal of Solid State Chemistry (2 papers)Radiotherapy and Oncology (2 papers)Medical Physics (1 paper)Engineering Applications of Artificial Intelligence (1 paper)
- Partner nations
- AustraliaUnited StatesNetherlands
In The Last Decade
Matthew Field
41 papers receiving 727 citations
Peers
Comparison fields: 5 of 105
- Health Informatics 55
- Radiology, Nuclear Medicine and Imaging 237
- Radiation 65
- Human-Computer Interaction 42
- Otorhinolaryngology 23
Countries citing papers authored by Matthew Field
This map shows the geographic impact of Matthew Field'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 Matthew Field with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew Field more than expected).
Fields of papers citing papers by Matthew Field
This network shows the impact of papers produced by Matthew Field. 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 Matthew Field. The network helps show where Matthew Field may publish in the future.
Co-authors
The 25 scholars most cited alongside Matthew Field, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 123 | |
| 2 | 2009 | 67 | |
| 3 | 2021 | 59 | |
| 4 | 2021 | 56 | |
| 5 | 2020 | 53 | |
| 6 | 2011 | 37 | |
| 7 | 2017 | 36 | |
| 8 | 2015 | 36 | |
| 9 | 2015 | 29 | |
| 10 | 2022 | 29 | |
| 11 | 2000 | 20 | |
| 12 | 2021 | 19 | |
| 13 | 2021 | 17 | |
| 14 | 2022 | 15 | |
| 15 | 2017 | 13 | |
| 16 | 2022 | 11 | |
| 17 | 2023 | 10 | |
| 18 | 2021 | 10 | |
| 19 | 2022 | 8 | |
| 20 | 2011 | 8 |
About Matthew Field
Matthew Field is a scholar working on Artificial Intelligence, Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging, Control and Systems Engineering and Computer Vision and Pattern Recognition, having authored 42 papers that have together received 745 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (11 papers), Lung Cancer Diagnosis and Treatment (10 papers), AI in cancer detection (7 papers), Anomaly Detection Techniques and Applications (5 papers), Time Series Analysis and Forecasting (4 papers), Head and Neck Cancer Studies (3 papers), Human Motion and Animation (3 papers) and Human Pose and Action Recognition (3 papers). The work is most often cited by research in Health Informatics (55 citations), Radiology, Nuclear Medicine and Imaging (237 citations), Radiation (65 citations), Human-Computer Interaction (42 citations) and Otorhinolaryngology (23 citations). Matthew Field has collaborated with scholars based in Australia, United States and Netherlands. Frequent co-authors include David Stirling, Lois Holloway, Fazel Naghdy, Zengxi Pan, Montserrat Ros, Martin Carolan, Michael Jameson, Shalini Vinod, Andrew Miller and Christian Ritz. Their work appears in journals such as Cancers, Journal of Solid State Chemistry, Radiotherapy and Oncology, Medical Physics and Engineering Applications of Artificial 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.