Harry Askham
Impact in
- Health Informatics top 0.1%
- Artificial Intelligence in Healthcare and Education
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- Retinal Imaging and Analysis
Papers in
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- Retinal Imaging and Analysis 3
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- Machine Learning in Healthcare 2
- Topic Modeling 1
- Text and Document Classification Technologies 1
- Co-authors
- Jon Crowcroft (1 shared paper)Daniele Quercia (1 shared paper)Reena Chopra (1 shared paper)Livia Faes (1 shared paper)Konstantinos Balaskas (1 shared paper)Siegfried K. Wagner (1 shared paper)Trevor Back (1 shared paper)Sam Blackwell (1 shared paper)
- Journals
- Nature Medicine (2 papers)Nature (1 paper)Investigative Ophthalmology & Visual Science (1 paper)Nature Protocols (1 paper)Journal of Medical Internet Research (1 paper)
- Partner nations
- United KingdomUnited States
In The Last Decade
Harry Askham
7 papers receiving 3.2k citations
Harry Askham's Hit Papers
Peers
Comparison fields: 5 of 139
- Health Informatics 678
- Radiology, Nuclear Medicine and Imaging 988
- Nephrology 264
- Health Information Management 208
- Ophthalmology 230
Countries citing papers authored by Harry Askham
This map shows the geographic impact of Harry Askham'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 Harry Askham with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Harry Askham more than expected).
Fields of papers citing papers by Harry Askham
This network shows the impact of papers produced by Harry Askham. 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 Harry Askham. The network helps show where Harry Askham may publish in the future.
Co-authors
The 10 scholars most cited alongside Harry Askham, 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 | Clinically applicable deep learning for diagnosis and referral in retinal disease Hit paper breakdown → | 2018 | 1929 |
| 2 | A clinically applicable approach to continuous prediction of future acute kidney injury Hit paper breakdown → | 2019 | 779 |
| 3 | Clinically Applicable Segmentation of Head and Neck Anatomy for Radiotherapy: Deep Learning Algorithm Development and Validation Study Hit paper breakdown → | 2021 | 244 |
| 4 | Predicting conversion to wet age-related macular degeneration using deep learning Hit paper breakdown → | 2020 | 227 |
| 5 | 2012 | 99 | |
| 6 | 2021 | 68 | |
| 7 | Diagnostic accuracy and interobserver variability of macular disease evaluation using optical coherence tomography | 2019 | 2 |
About Harry Askham
Harry Askham is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, General Social Sciences, Ophthalmology and Computer Vision and Pattern Recognition, having authored 7 papers that have together received 3.3k indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (3 papers), Machine Learning in Healthcare (2 papers), Topic Modeling (1 paper), Retinal Diseases and Treatments (1 paper), Text and Document Classification Technologies (1 paper), Computational and Text Analysis Methods (1 paper) and Medical Image Segmentation Techniques (1 paper). The work is most often cited by research in Health Informatics (678 citations), Radiology, Nuclear Medicine and Imaging (988 citations), Nephrology (264 citations), Health Information Management (208 citations) and Ophthalmology (230 citations). Harry Askham has collaborated with scholars based in United Kingdom and United States. Frequent co-authors include Jon Crowcroft, Daniele Quercia, Reena Chopra, Livia Faes, Konstantinos Balaskas, Siegfried K. Wagner, Trevor Back, Sam Blackwell, Pearse Andrew Keane and Joseph R. E. Ledsam. Their work appears in journals such as Nature Medicine, Nature, Investigative Ophthalmology & Visual Science, Nature Protocols and Journal of Medical Internet Research.
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.