Alanna Vial
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
- Medical Imaging Techniques and Applications
Papers in
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- Radiomics and Machine Learning in Medical Imaging 5
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- AI in cancer detection 4
- Anomaly Detection Techniques and Applications 1
- Co-authors
- Geoffrey Currie (1 shared paper)K. Elizabeth Hawk (1 shared paper)Ran Klein (1 shared paper)Eric Rohren (1 shared paper)Martin Carolan (4 shared papers)Matthew Field (5 shared papers)Lois Holloway (4 shared papers)Montserrat Ros (5 shared papers)
- Journals
- Obstetrical & Gynecological Survey (1 paper)Translational Cancer Research (1 paper)Journal of medical imaging and radiation sciences (1 paper)Research Online (University of Wollongong) (2 papers)
- Partner nations
- AustraliaUnited StatesCanada
In The Last Decade
Alanna Vial
7 papers receiving 430 citations
Peers
Comparison fields: 5 of 107
- Health Informatics 75
- Radiology, Nuclear Medicine and Imaging 199
- Health Information Management 28
- Artificial Intelligence 104
- Neurology 21
Countries citing papers authored by Alanna Vial
This map shows the geographic impact of Alanna Vial'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 Alanna Vial with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alanna Vial more than expected).
Fields of papers citing papers by Alanna Vial
This network shows the impact of papers produced by Alanna Vial. 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 Alanna Vial. The network helps show where Alanna Vial may publish in the future.
Co-authors
The 14 scholars most cited alongside Alanna Vial, 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 | 2019 | 294 | |
| 2 | 2018 | 123 | |
| 3 | 2018 | 15 | |
| 4 | 1960 | 6 | |
| 5 | 2019 | 6 | |
| 6 | 2017 | 4 | |
| 7 | 2018 | 1 | |
| 8 | 2017 | 0 |
About Alanna Vial
Alanna Vial is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Pulmonary and Respiratory Medicine, Biomedical Engineering and Computer Vision and Pattern Recognition, having authored 8 papers that have together received 449 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (5 papers), AI in cancer detection (4 papers), Advanced X-ray and CT Imaging (2 papers), Lung Cancer Diagnosis and Treatment (2 papers), Artificial Intelligence in Healthcare and Education (1 paper), Anomaly Detection Techniques and Applications (1 paper), Gastric Cancer Management and Outcomes (1 paper) and Virtual Reality Applications and Impacts (1 paper). The work is most often cited by research in Health Informatics (75 citations), Radiology, Nuclear Medicine and Imaging (199 citations), Health Information Management (28 citations), Artificial Intelligence (104 citations) and Neurology (21 citations). Alanna Vial has collaborated with scholars based in Australia, United States and Canada. Frequent co-authors include Geoffrey Currie, K. Elizabeth Hawk, Ran Klein, Eric Rohren, Martin Carolan, Matthew Field, Lois Holloway, Montserrat Ros, David Stirling and Andrew Miller. Their work appears in journals such as Obstetrical & Gynecological Survey, Translational Cancer Research, Journal of medical imaging and radiation sciences and Research Online (University of Wollongong).
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.