Warren Clarida

1.3k citations
4 papers · 807 · 1 hit paper · h-index 3

Impact in

    • Retinal Diseases and Treatments
    • Retinal and Optic Conditions
    • Glaucoma and retinal disorders
    • Artificial Intelligence in Healthcare and Education

Papers in

Warren Clarida

4 papers receiving 768 citations

Warren Clarida's Hit Papers

Improved Automated Detection of Diabetic Retinopathy on a Publicly Available Dataset Through Integration of Deep Learning 2016 · 751 citations
7510+3+6Years since publication250500750

Peers

Warren Clarida
Comparison fields: 5 of 57
  • Ophthalmology 386
  • Health Informatics 52
  • Radiology, Nuclear Medicine and Imaging 602
  • Health Information Management 87
  • Computer Vision and Pattern Recognition 174
Replace Haslina Hamzah with:
Haslina Hamzah Singapore
Valentina Bellemo Singapore
Jane Scheetz Australia
Jaemin Son South Korea
T. Y. Alvin Liu United States
Samantha Mann United Kingdom
Geunyoung Lee Singapore
Lanqin Zhao China
Katia Charrière France
Fangyao Tang Hong Kong
Warren Clarida relative to Haslina Hamzah Singapore Haslina Hamzah's profile →
Citations per field
00.5×3.1×
Haslina Hamzah · 1×
Citations per year

Countries citing papers authored by Warren Clarida

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authors

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.

Border = papers with Warren Clarida Line = papers co-authored together Warren Clarida links everyone, so they are left out of the graph.

All Works

4 of 4 papers shown

About Warren Clarida

Warren Clarida is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology, Computer Vision and Pattern Recognition, Health, Toxicology and Mutagenesis and Health Informatics, having authored 4 papers that have together received 807 indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (3 papers), Retinal and Optic Conditions (2 papers), Artificial Intelligence in Healthcare and Education (1 paper), Retinal Diseases and Treatments (1 paper), Digital Imaging for Blood Diseases (1 paper) and Health, Environment, Cognitive Aging (1 paper). The work is most often cited by research in Ophthalmology (386 citations), Health Informatics (52 citations), Radiology, Nuclear Medicine and Imaging (602 citations), Health Information Management (87 citations) and Computer Vision and Pattern Recognition (174 citations). Warren Clarida has collaborated with scholars based in United States, Netherlands and France. Frequent co-authors include Michael D. Abràmoff, James C. Folk, Meindert Niemeijer, Ryan Amelon, Ali Erginay, Yiyue Lou, Harold P. Lehmann, Roomasa Channa, Risa M. Wolf and Stephen R. Russell. Their work appears in journals such as npj Digital Medicine, Investigative Ophthalmology & Visual Science 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.

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