Warren Clarida
Impact in
- Ophthalmology top 1%
- Retinal Diseases and Treatments
- Retinal and Optic Conditions
- Glaucoma and retinal disorders
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
Papers in
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- Artificial Intelligence in Healthcare and Education 1
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- Retinal and Optic Conditions 2
- Retinal Diseases and Treatments 2
- Co-authors
- Michael D. AbràmoffRyan AmelonJames C. FolkMeindert NiemeijerAli ErginayYiyue LouRoomasa ChannaHarold P. Lehmann
- Journals
- Investigative Ophthalmology & Visual Science (1 paper)npj Digital Medicine (1 paper)Archivos de la Sociedad Española de Oftalmología (English Edition) (1 paper)
- Partner nations
- United StatesNetherlandsFrance
In The Last Decade
Warren Clarida
4 papers receiving 742 citations
Hit Papers
Peers
Comparison fields: 5 of 61
- Ophthalmology 533
- Health Informatics 57
- Radiology, Nuclear Medicine and Imaging 675
- Health Information Management 99
- Computer Vision and Pattern Recognition 186
Countries citing papers authored by Warren Clarida
This map shows the geographic impact of Warren Clarida'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 Warren Clarida with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Warren Clarida more than expected).
Fields of papers citing papers by Warren Clarida
This network shows the impact of papers produced by Warren Clarida. 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 Warren Clarida. The network helps show where Warren Clarida may publish in the future.
Co-authorship network
The 16 scholars most cited alongside Warren Clarida, 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 | 2022 | 29 | |
| 2 | 2020 | 2 | |
| 3 | 2018 | 24 | |
| 4 | Improved Automated Detection of Diabetic Retinopathy on a Publicly Available Dataset Through Integration of Deep Learning Hit paper breakdown → | 2016 | 726 |
About Warren Clarida
Warren Clarida is a scholar working on Health Informatics, Ophthalmology, Radiology, Nuclear Medicine and Imaging, Health, Toxicology and Mutagenesis and Computer Vision and Pattern Recognition, having authored 4 papers that have together received 781 indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (3 papers), Retinal and Optic Conditions (2 papers), Retinal Diseases and Treatments (2 papers), Artificial Intelligence in Healthcare and Education (1 paper), Health, Environment, Cognitive Aging (1 paper), Acute Ischemic Stroke Management (1 paper) and Digital Imaging for Blood Diseases (1 paper). The work is most often cited by research in Ophthalmology (533 citations), Health Informatics (57 citations), Radiology, Nuclear Medicine and Imaging (675 citations), Health Information Management (99 citations) and Computer Vision and Pattern Recognition (186 citations). Warren Clarida has collaborated with scholars based in United States, Netherlands and France. Frequent co-authors include Michael D. Abràmoff, Ryan Amelon, James C. Folk, Meindert Niemeijer, Ali Erginay, Yiyue Lou, Roomasa Channa, Harold P. Lehmann, Risa M. Wolf and Stephen R. Russell. Their work appears in journals such as Investigative Ophthalmology & Visual Science, npj Digital Medicine and Archivos de la Sociedad Española de Oftalmología (English Edition).
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.