Daniel Kermany
Impact in
- Health Informatics top 5%
-
- COVID-19 diagnosis using AI
- Radiomics and Machine Learning in Medical Imaging
- Retinal Imaging and Analysis
Papers in
-
- Retinal Development and Disorders 1
- Single-cell and spatial transcriptomics 1
- Gut microbiota and health 1
- Surgery 2
- Coronary Interventions and Diagnostics 2
- Co-authors
- Sepehr Bahadorani (2 shared papers)Michael Singer (2 shared papers)Kang Zhang (2 shared papers)Gen Li (1 shared paper)Yaoming Liu (1 shared paper)Tao Wen (1 shared paper)Jie Zhu (1 shared paper)Viet Anh Nguyen Huu (1 shared paper)
- Journals
- Cancer Communications (1 paper)Ophthalmic surgery, lasers & imaging retina (1 paper)Clinical ophthalmology (1 paper)Precision Clinical Medicine (1 paper)Data Archiving and Networked Services (DANS) (3 papers)
- Partner nations
- United StatesChinaMacao
In The Last Decade
Daniel Kermany
8 papers receiving 691 citations
Daniel Kermany's Hit Papers
Peers
Comparison fields: 5 of 65
- Health Informatics 46
- Radiology, Nuclear Medicine and Imaging 569
- Artificial Intelligence 380
- Ophthalmology 81
- Health Information Management 33
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 | Labeled Optical Coherence Tomography (OCT) and Chest X-Ray Images for Classification Hit paper breakdown → | 2018 | 548 |
| 2 | 2018 | 123 | |
| 3 | 2018 | 24 | |
| 4 | 2022 | 18 | |
| 5 | 2018 | 10 | |
| 6 | 2019 | 5 | |
| 7 | 2025 | 1 | |
| 8 | 2017 | 1 |
About Daniel Kermany
Daniel Kermany is a scholar working on Molecular Biology, Surgery, Biomedical Engineering, Neurology and Ophthalmology, having authored 8 papers that have together received 730 indexed citations. Recurring topics across this work include Optical Coherence Tomography Applications (2 papers), Coronary Interventions and Diagnostics (2 papers), Retinal Diseases and Treatments (1 paper), Retinal Development and Disorders (1 paper), Global Cancer Incidence and Screening (1 paper), Single-cell and spatial transcriptomics (1 paper), Gut microbiota and health (1 paper) and Barrier Structure and Function Studies (1 paper). The work is most often cited by research in Health Informatics (46 citations), Radiology, Nuclear Medicine and Imaging (569 citations), Artificial Intelligence (380 citations), Ophthalmology (81 citations) and Health Information Management (33 citations). Daniel Kermany has collaborated with scholars based in United States, China and Macao. Frequent co-authors include Sepehr Bahadorani, Michael Singer, Kang Zhang, Gen Li, Yaoming Liu, Tao Wen, Jie Zhu, Viet Anh Nguyen Huu, Shu-fang Deng and Charlotte L Zhang. Their work appears in journals such as Cancer Communications, Ophthalmic surgery, lasers & imaging retina, Clinical ophthalmology, Precision Clinical Medicine and Data Archiving and Networked Services (DANS).
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.