Dale R. Webster
- Radiology, Nuclear Medicine and Imaging top 0.1%
- Ophthalmology top 0.1%
- Artificial Intelligence top 0.5%
- Molecular Biology top 10%
- Computer Vision and Pattern Recognition top 1%
- Co-authors
- Lily PengKasumi WidnerVarun GulshanDerek WuSubhashini VenugopalanKim RamasamyRajiv RamanArunachalam Narayanaswamy
- Topics
- Retinal Imaging and Analysis (20 papers)Retinal Diseases and Treatments (11 papers)Artificial Intelligence in Healthcare and Education (7 papers)
- Partner nations
- United StatesIndiaCanada
In The Last Decade
Dale R. Webster
36 papers receiving 8.8k citations
Hit Papers
Peers
Comparison fields: 5 of 194
- Radiology, Nuclear Medicine and Imaging 4.7k
- Ophthalmology 2.7k
- Artificial Intelligence 1.7k
- Molecular Biology 1.3k
- Computer Vision and Pattern Recognition 1.1k
Countries citing papers authored by Dale R. Webster
This map shows the geographic impact of Dale R. Webster'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 Dale R. Webster with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dale R. Webster more than expected).
Fields of papers citing papers by Dale R. Webster
This network shows the impact of papers produced by Dale R. Webster. 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 Dale R. Webster. The network helps show where Dale R. Webster may publish in the future.
Co-authorship network of co-authors of Dale R. Webster
This figure shows the co-authorship network connecting the top 25 collaborators of Dale R. Webster. A scholar is included among the top collaborators of Dale R. Webster based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Dale R. Webster. Dale R. Webster is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 12 | |
| 6 | 25 | |
| 7 | 2 | |
| 8 | 20 | |
| 9 | 5 | |
| 10 | 31 | |
| 11 | 90 | |
| 12 | 12 | |
| 13 | Deep Learning for Identifying Retinal Vein Occlusion Features in Fundus Images | 0 |
| 14 | A Study of Feature-based Consensus Formation for Glaucoma Risk Assessment | 1 |
| 15 | Asynchronous Remote Adjudication for Grading Diabetic Retinopathy | 1 |
| 16 | 126 | |
| 17 | Assisted reads for diabetic retinopathy using a deep learning algorithm and integrated gradient explanation | 2 |
| 18 | Grader Variability and the Importance of Reference Standards for Evaluating Machine Learning Models for Diabetic Retinopathybreakdown → | 358 |
| 19 | 17 | |
| 20 | 77 |
About Dale R. Webster
Dale R. Webster is a scholar working on Health Informatics, Ophthalmology and Radiology, Nuclear Medicine and Imaging, having authored 40 papers that have together received 9.2k indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (20 papers), Retinal Diseases and Treatments (11 papers) and Artificial Intelligence in Healthcare and Education (7 papers). The work is most often cited by research in Health Informatics (1.0k citations), Ophthalmology (2.7k citations) and Radiology, Nuclear Medicine and Imaging (4.7k citations). Dale R. Webster has collaborated with scholars based in United States, India and Canada. Frequent co-authors include Lily Peng, Kasumi Widner, Varun Gulshan, Derek Wu, Subhashini Venugopalan, Kim Ramasamy, Rajiv Raman, Arunachalam Narayanaswamy, Marc Coram and Jorge Cuadros. Their work appears in journals such as New England Journal of Medicine, JAMA and Nature Medicine.
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.