Kasumi Widner
- Health Informatics top 0.05%
- Ophthalmology top 0.2%
- Retinal Diseases and Treatments 4
- Retinal and Optic Conditions 2
- Health Information Management top 0.1%
- Artificial Intelligence in Healthcare 2
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- Retinal Imaging and Analysis 7
- COVID-19 diagnosis using AI 2
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- Non-Invasive Vital Sign Monitoring 1
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- Machine Learning in Healthcare 1
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- Acute Ischemic Stroke Management 1
- Co-authors
- Dale R. WebsterLily PengVarun GulshanKim RamasamyDerek WuMarc CoramRajiv RamanSubhashini Venugopalan
- Journals
- JAMA (1 paper)JAMA Network Open (1 paper)Investigative Ophthalmology & Visual Science (1 paper)
- Partner nations
- United StatesIndia
In The Last Decade
Kasumi Widner
7 papers receiving 4.9k citations
Hit Papers
Peers
Comparison fields: 5 of 164
- Health Informatics 703
- Ophthalmology 1.8k
- Health Information Management 665
- Radiology, Nuclear Medicine and Imaging 3.2k
- Computer Vision and Pattern Recognition 806
Countries citing papers authored by Kasumi Widner
This map shows the geographic impact of Kasumi Widner'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 Kasumi Widner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kasumi Widner more than expected).
Fields of papers citing papers by Kasumi Widner
This network shows the impact of papers produced by Kasumi Widner. 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 Kasumi Widner. The network helps show where Kasumi Widner may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Kasumi Widner, 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 | 2025 | 1 | |
| 2 | 2025 | 2 | |
| 3 | 2023 | 33 | |
| 4 | Challenges in evaluating clinical deployments of Deep Learning Assisted Diagnostics for Diabetic Retinopathy Screening | 2020 | 2 |
| 5 | 2019 | 181 | |
| 6 | Grader Variability and the Importance of Reference Standards for Evaluating Machine Learning Models for Diabetic Retinopathybreakdown → | 2018 | 358 |
| 7 | Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographsbreakdown → | 2016 | 4490 |
About Kasumi Widner
Kasumi Widner is a scholar working on Health Informatics, Ophthalmology, Health Information Management, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence, having authored 7 papers that have together received 5.1k indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (7 papers), Retinal Diseases and Treatments (4 papers), Retinal and Optic Conditions (2 papers), Artificial Intelligence in Healthcare (2 papers), COVID-19 diagnosis using AI (2 papers), Non-Invasive Vital Sign Monitoring (1 paper), Machine Learning in Healthcare (1 paper) and Acute Ischemic Stroke Management (1 paper). The work is most often cited by research in Health Informatics (703 citations), Ophthalmology (1.8k citations), Health Information Management (665 citations), Radiology, Nuclear Medicine and Imaging (3.2k citations) and Computer Vision and Pattern Recognition (806 citations). Kasumi Widner has collaborated with scholars based in United States and India. Frequent co-authors include Dale R. Webster, Lily Peng, Varun Gulshan, Kim Ramasamy, Derek Wu, Marc Coram, Rajiv Raman, Subhashini Venugopalan, Martin C. Stumpe and Arunachalam Narayanaswamy. Their work appears in journals such as JAMA, JAMA Network Open, Investigative Ophthalmology & Visual Science, Ophthalmology 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.