Terry Spitz
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
- Ophthalmology top 5%
- Retinal Diseases and Treatments
- Ophthalmology and Visual Health Research
Papers in
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- Artificial Intelligence in Healthcare and Education 5
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- Retinal Imaging and Analysis 5
- Co-authors
- Reena Chopra (3 shared papers)Gabriella Moraes (3 shared papers)Christopher J. Kelly (2 shared papers)Daniel Ferraz (2 shared papers)Pearse Andrew Keane (3 shared papers)Hagar Khalid (2 shared papers)Praveen J. Patel (3 shared papers)Tiarnán D L Keenan (3 shared papers)
- Journals
- Nature Medicine (2 papers)EClinicalMedicine (1 paper)Ophthalmology (1 paper)Investigative Ophthalmology & Visual Science (1 paper)EBioMedicine (1 paper)
- Partner nations
- United StatesUnited KingdomBrazil
In The Last Decade
Terry Spitz
9 papers receiving 478 citations
Terry Spitz's Hit Papers
Peers
Comparison fields: 5 of 59
- Health Informatics 146
- Ophthalmology 109
- Radiology, Nuclear Medicine and Imaging 216
- Health Information Management 24
- Statistics, Probability and Uncertainty 14
Countries citing papers authored by Terry Spitz
This map shows the geographic impact of Terry Spitz'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 Terry Spitz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Terry Spitz more than expected).
Fields of papers citing papers by Terry Spitz
This network shows the impact of papers produced by Terry Spitz. 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 Terry Spitz. The network helps show where Terry Spitz may publish in the future.
Co-authors
The 19 scholars most cited alongside Terry Spitz, 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 | Predicting conversion to wet age-related macular degeneration using deep learning Hit paper breakdown → | 2020 | 227 |
| 2 | 2020 | 105 | |
| 3 | 2023 | 91 | |
| 4 | 2022 | 31 | |
| 5 | 2024 | 25 | |
| 6 | 2025 | 3 | |
| 7 | 2021 | 2 | |
| 8 | Quantitative analysis of change in retinal tissues in neovascular age-related macular degeneration using artificial intelligence | 2020 | 1 |
| 9 | 2020 | 1 |
About Terry Spitz
Terry Spitz is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging, Safety Research, Oncology and Artificial Intelligence, having authored 9 papers that have together received 486 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (5 papers), Retinal Imaging and Analysis (5 papers), Ethics and Social Impacts of AI (1 paper), Cutaneous Melanoma Detection and Management (1 paper) and AI in cancer detection (1 paper). The work is most often cited by research in Health Informatics (146 citations), Ophthalmology (109 citations), Radiology, Nuclear Medicine and Imaging (216 citations), Health Information Management (24 citations) and Statistics, Probability and Uncertainty (14 citations). Terry Spitz has collaborated with scholars based in United States, United Kingdom and Brazil. Frequent co-authors include Reena Chopra, Gabriella Moraes, Christopher J. Kelly, Daniel Ferraz, Pearse Andrew Keane, Hagar Khalid, Praveen J. Patel, Tiarnán D L Keenan, Livia Faes and Siegfried K. Wagner. Their work appears in journals such as Nature Medicine, EClinicalMedicine, Ophthalmology, Investigative Ophthalmology & Visual Science and EBioMedicine.
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.