Skylar E. Stolte
Impact in
- Ophthalmology top 5%
- Retinal Diseases and Treatments
- Retinal and Optic Conditions
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- Retinal Imaging and Analysis
- Radiomics and Machine Learning in Medical Imaging
Papers in
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- Retinal Imaging and Analysis 3
- Radiomics and Machine Learning in Medical Imaging 2
- COVID-19 diagnosis using AI 2
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- Transcranial Magnetic Stimulation Studies 4
- Brain Tumor Detection and Classification 2
- Co-authors
- Ruogu Fang (13 shared papers)Ling Dai (1 shared paper)Weiping Jia (1 shared paper)Bin Sheng (1 shared paper)Huating Li (1 shared paper)Dinggang Shen (1 shared paper)Adam J. Woods (8 shared papers)Aprinda Indahlastari (9 shared papers)
- Journals
- Medical Image Analysis (3 papers)Brain stimulation (3 papers)BMC Medical Informatics and Decision Making (1 paper)Frontiers in Neurology (1 paper)Lecture notes in computer science (2 papers)
- Partner nations
- United StatesHong KongBrazil
In The Last Decade
Skylar E. Stolte
12 papers receiving 296 citations
Peers
Comparison fields: 5 of 50
- Ophthalmology 86
- Radiology, Nuclear Medicine and Imaging 181
- Neurology 66
- Health Informatics 10
- Health Information Management 30
Countries citing papers authored by Skylar E. Stolte
This map shows the geographic impact of Skylar E. Stolte'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 Skylar E. Stolte with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Skylar E. Stolte more than expected).
Fields of papers citing papers by Skylar E. Stolte
This network shows the impact of papers produced by Skylar E. Stolte. 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 Skylar E. Stolte. The network helps show where Skylar E. Stolte may publish in the future.
Co-authors
The 25 scholars most cited alongside Skylar E. Stolte, 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 | 2020 | 101 | |
| 2 | 2020 | 78 | |
| 3 | 2020 | 55 | |
| 4 | 2024 | 24 | |
| 5 | 2019 | 17 | |
| 6 | 2023 | 9 | |
| 7 | 2022 | 8 | |
| 8 | 2024 | 5 | |
| 9 | 2024 | 3 | |
| 10 | 2022 | 2 | |
| 11 | 2023 | 1 | |
| 12 | 2023 | 1 | |
| 13 | 2000 | 1 | |
| 14 | 2025 | 0 | |
| 15 | 2026 | 0 |
About Skylar E. Stolte
Skylar E. Stolte is a scholar working on Radiology, Nuclear Medicine and Imaging, Neurology, Computer Vision and Pattern Recognition, Artificial Intelligence and Ophthalmology, having authored 15 papers that have together received 305 indexed citations. Recurring topics across this work include Transcranial Magnetic Stimulation Studies (4 papers), Retinal Imaging and Analysis (3 papers), Medical Image Segmentation Techniques (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Retinal Diseases and Treatments (2 papers), Brain Tumor Detection and Classification (2 papers), Retinal and Optic Conditions (2 papers) and COVID-19 diagnosis using AI (2 papers). The work is most often cited by research in Ophthalmology (86 citations), Radiology, Nuclear Medicine and Imaging (181 citations), Neurology (66 citations), Health Informatics (10 citations) and Health Information Management (30 citations). Skylar E. Stolte has collaborated with scholars based in United States, Hong Kong and Brazil. Frequent co-authors include Ruogu Fang, Ling Dai, Weiping Jia, Bin Sheng, Huating Li, Dinggang Shen, Adam J. Woods, Aprinda Indahlastari, Alejandro Albizu and Nicole R. Nissim. Their work appears in journals such as Medical Image Analysis, Brain stimulation, BMC Medical Informatics and Decision Making, Frontiers in Neurology and Lecture notes in computer science.
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.