Kasumi Widner

8.4k total citations · 2 hit papers
7 papers, 5.1k citations indexed

About

Kasumi Widner is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology and Health Information Management. According to data from OpenAlex, Kasumi Widner has authored 7 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Radiology, Nuclear Medicine and Imaging, 4 papers in Ophthalmology and 2 papers in Health Information Management. Recurrent topics in Kasumi Widner's work include Retinal Imaging and Analysis (7 papers), Retinal Diseases and Treatments (4 papers) and Retinal and Optic Conditions (2 papers). Kasumi Widner is often cited by papers focused on Retinal Imaging and Analysis (7 papers), Retinal Diseases and Treatments (4 papers) and Retinal and Optic Conditions (2 papers). Kasumi Widner collaborates with scholars based in United States and India. Kasumi Widner's 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 and has published in prestigious journals such as JAMA, Nature Medicine and Ophthalmology.

In The Last Decade

Kasumi Widner

7 papers receiving 4.9k citations

Hit Papers

Development and Validation of a Deep Learning Algorithm f... 2016 2026 2019 2022 2016 2018 1000 2.0k 3.0k 4.0k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Kasumi Widner United States 4 3.2k 1.8k 1.2k 806 703 7 5.1k
Derek Wu Canada 9 3.2k 1.0× 1.7k 0.9× 1.2k 1.0× 774 1.0× 706 1.0× 18 5.1k
Jorge Cuadros United States 14 3.5k 1.1× 2.0k 1.1× 1.2k 1.0× 836 1.0× 667 0.9× 32 5.3k
T. Madams United States 3 2.8k 0.9× 1.4k 0.8× 1.1k 0.9× 716 0.9× 627 0.9× 6 4.5k
Arunachalam Narayanaswamy United States 12 3.0k 0.9× 1.6k 0.9× 1.2k 1.0× 852 1.1× 678 1.0× 15 5.3k
Marc Coram United States 19 2.9k 0.9× 1.6k 0.9× 1.2k 1.0× 740 0.9× 648 0.9× 30 6.2k
Varun Gulshan United States 8 3.2k 1.0× 1.8k 1.0× 1.4k 1.2× 1.5k 1.9× 690 1.0× 9 5.8k
Kim Ramasamy India 28 4.3k 1.3× 3.5k 2.0× 1.2k 0.9× 760 0.9× 658 0.9× 141 7.1k
Yun Liu United States 29 2.4k 0.7× 719 0.4× 2.0k 1.6× 847 1.1× 877 1.2× 112 5.4k
Rajiv Raman India 34 5.6k 1.7× 4.5k 2.6× 1.2k 1.0× 896 1.1× 701 1.0× 232 8.8k
Alastair K. Denniston United Kingdom 42 2.3k 0.7× 2.8k 1.6× 917 0.7× 192 0.2× 1.3k 1.8× 221 6.6k

Countries citing papers authored by Kasumi Widner

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of Kasumi Widner

This figure shows the co-authorship network connecting the top 25 collaborators of Kasumi Widner. A scholar is included among the top collaborators of Kasumi Widner 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 Kasumi Widner. Kasumi Widner is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

7 of 7 papers shown
1.
Brant, Arthur, Preeti Singh, Xiang Yin, et al.. (2025). Performance of a Deep Learning Diabetic Retinopathy Algorithm in India. JAMA Network Open. 8(3). e250984–e250984. 1 indexed citations
2.
Praveen, Pradeep A., Arthur Brant, Xiang Yin, et al.. (2025). Validation of a Deep Learning Model for Diabetic Retinopathy on Patients with Young-Onset Diabetes. Ophthalmology and Therapy. 14(5). 1147–1155. 2 indexed citations
3.
Widner, Kasumi, Sunny Virmani, Jonathan Krause, et al.. (2023). Lessons learned from translating AI from development to deployment in healthcare. Nature Medicine. 29(6). 1304–1306. 33 indexed citations
4.
Sayres, Rory, et al.. (2020). Challenges in evaluating clinical deployments of Deep Learning Assisted Diagnostics for Diabetic Retinopathy Screening. Investigative Ophthalmology & Visual Science. 61(7). 2045–2045. 2 indexed citations
5.
Gulshan, Varun, Renu P. Rajan, Kasumi Widner, et al.. (2019). Performance of a Deep-Learning Algorithm vs Manual Grading for Detecting Diabetic Retinopathy in India. JAMA Ophthalmology. 137(9). 987–987. 181 indexed citations
6.
Krause, Jonathan, Varun Gulshan, Ehsan Rahimy, et al.. (2018). Grader Variability and the Importance of Reference Standards for Evaluating Machine Learning Models for Diabetic Retinopathy. Ophthalmology. 125(8). 1264–1272. 358 indexed citations breakdown →
7.
Gulshan, Varun, Lily Peng, Marc Coram, et al.. (2016). Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs. JAMA. 316(22). 2402–2402. 4490 indexed citations breakdown →

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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