Darvin Yi
- Radiology, Nuclear Medicine and Imaging top 2%
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Ophthalmology top 2%
- Pulmonary and Respiratory Medicine
- Co-authors
- Daniel L. RubinCarson LamZeshan HussainFrancisco Javier Giménez Fuentes‐GuerraTony LindseyMargaret GuoEndre GrøvikElizabeth Tong
- Topics
- Retinal Imaging and Analysis (12 papers)Radiomics and Machine Learning in Medical Imaging (4 papers)Glaucoma and retinal disorders (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaRadiologyPLoS Biology
- Partner nations
- United StatesNorwayItaly
In The Last Decade
Darvin Yi
20 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 125
- Radiology, Nuclear Medicine and Imaging 778
- Artificial Intelligence 359
- Computer Vision and Pattern Recognition 246
- Ophthalmology 212
- Pulmonary and Respiratory Medicine 184
Countries citing papers authored by Darvin Yi
This map shows the geographic impact of Darvin Yi'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 Darvin Yi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Darvin Yi more than expected).
Fields of papers citing papers by Darvin Yi
This network shows the impact of papers produced by Darvin Yi. 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 Darvin Yi. The network helps show where Darvin Yi may publish in the future.
Co-authorship network of co-authors of Darvin Yi
This figure shows the co-authorship network connecting the top 25 collaborators of Darvin Yi. A scholar is included among the top collaborators of Darvin Yi 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 Darvin Yi. Darvin Yi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 4 | |
| 4 | 20 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | 2 | |
| 8 | 9 | |
| 9 | 20 | |
| 10 | 12 | |
| 11 | 2 | |
| 12 | 29 | |
| 13 | 32 | |
| 14 | AutoPtosis: A dual model system for rapid and automatic detection of ptosis | 1 |
| 15 | 83 | |
| 16 | 170 | |
| 17 | 150 | |
| 18 | Opening the Black Box: Visualization of Deep Neural Network for Detection of Disease in Retinal Fundus Photographs | 0 |
| 19 | 29 | |
| 20 | Differential Data Augmentation Techniques for Medical Imaging Classification Tasks. | 215 |
About Darvin Yi
Darvin Yi is a scholar working on Health Informatics, Ophthalmology and Radiology, Nuclear Medicine and Imaging, having authored 26 papers that have together received 1.2k indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (12 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Glaucoma and retinal disorders (4 papers). The work is most often cited by research in Health Informatics (134 citations), Radiology, Nuclear Medicine and Imaging (778 citations) and Ophthalmology (212 citations). Darvin Yi has collaborated with scholars based in United States, Norway and Italy. Frequent co-authors include Daniel L. Rubin, Carson Lam, Zeshan Hussain, Francisco Javier Giménez Fuentes‐Guerra, Tony Lindsey, Margaret Guo, Endre Grøvik, Elizabeth Tong, Michael Iv and Greg Zaharchuk. Their work appears in journals such as SHILAP Revista de lepidopterología, Radiology and PLoS Biology.
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.