Daniel Kermany
Impact in
- Health Informatics top 0.2%
- Artificial Intelligence in Healthcare and Education
-
- COVID-19 diagnosis using AI
- Retinal Imaging and Analysis
- Radiomics and Machine Learning in Medical Imaging
Papers in
-
- Glaucoma and retinal disorders 2
- Retinal and Optic Conditions 2
- Retinal Diseases and Treatments 2
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- COVID-19 diagnosis using AI 2
- Retinal Imaging and Analysis 2
- Co-authors
- Michael A. Singer (3 shared papers)Sepehr Bahadorani (2 shared papers)Kang Zhang (2 shared papers)Viet Anh Nguyen Huu (1 shared paper)Gen Li (1 shared paper)Runze Zhang (1 shared paper)Shida Chen (1 shared paper)Shu-fang Deng (1 shared paper)
- Journals
- Ophthalmic surgery, lasers & imaging retina (1 paper)Nature Medicine (1 paper)Clinical ophthalmology (1 paper)Cell (1 paper)癌症：英文版 (1 paper)
- Partner nations
- United StatesChinaMacao
In The Last Decade
Daniel Kermany
12 papers receiving 4.8k citations
Daniel Kermany's Hit Papers
Peers
Comparison fields: 5 of 182
- Health Informatics 389
- Radiology, Nuclear Medicine and Imaging 3.0k
- Ophthalmology 686
- Health Information Management 307
- Artificial Intelligence 1.8k
Countries citing papers authored by Daniel Kermany
This map shows the geographic impact of Daniel Kermany'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 Daniel Kermany with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Kermany more than expected).
Fields of papers citing papers by Daniel Kermany
This network shows the impact of papers produced by Daniel Kermany. 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 Daniel Kermany. The network helps show where Daniel Kermany may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Kermany, 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 | Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning Hit paper breakdown → | 2018 | 3466 |
| 2 | Labeled Optical Coherence Tomography (OCT) and Chest X-Ray Images for Classification Hit paper breakdown → | 2018 | 564 |
| 3 | 2019 | 479 | |
| 4 | Deep-learning models for the detection and incidence prediction of chronic kidney disease and type 2 diabetes from retinal fundus images Hit paper breakdown → | 2021 | 237 |
| 5 | 2018 | 125 | |
| 6 | 2016 | 35 | |
| 7 | 2018 | 24 | |
| 8 | 2022 | 19 | |
| 9 | 2018 | 10 | |
| 10 | 2019 | 5 | |
| 11 | 2025 | 2 | |
| 12 | 2017 | 1 |
About Daniel Kermany
Daniel Kermany is a scholar working on Ophthalmology, Radiology, Nuclear Medicine and Imaging, Health Informatics, Health Information Management and Neurology, having authored 12 papers that have together received 5.0k indexed citations. Recurring topics across this work include Optical Coherence Tomography Applications (2 papers), Glaucoma and retinal disorders (2 papers), COVID-19 diagnosis using AI (2 papers), Coronary Interventions and Diagnostics (2 papers), Retinal and Optic Conditions (2 papers), Retinal Diseases and Treatments (2 papers), Retinal Imaging and Analysis (2 papers) and CRISPR and Genetic Engineering (1 paper). The work is most often cited by research in Health Informatics (389 citations), Radiology, Nuclear Medicine and Imaging (3.0k citations), Ophthalmology (686 citations), Health Information Management (307 citations) and Artificial Intelligence (1.8k citations). Daniel Kermany has collaborated with scholars based in United States, China and Macao. Frequent co-authors include Michael A. Singer, Sepehr Bahadorani, Kang Zhang, Viet Anh Nguyen Huu, Gen Li, Runze Zhang, Shida Chen, Shu-fang Deng, yayi wang and Fei Li. Their work appears in journals such as Ophthalmic surgery, lasers & imaging retina, Nature Medicine, Clinical ophthalmology, Cell and 癌症：英文版.
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.