David Coz
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
- Ophthalmology top 5%
- Retinal Diseases and Treatments
- Retinal and Optic Conditions
- Glaucoma and retinal disorders
Papers in
-
- AI in cancer detection 1
- Machine Learning and Data Classification 1
- Oncology 2
- Cutaneous Melanoma Detection and Management 2
- Co-authors
- Lily Peng (3 shared papers)Dale R. Webster (3 shared papers)Greg S. Corrado (2 shared papers)Rory Sayres (3 shared papers)Scott Barb (1 shared paper)Anthony Joseph (1 shared paper)Arunachalam Narayanaswamy (2 shared papers)Jonathan Krause (2 shared papers)
- Journals
- JAMA Network Open (1 paper)Investigative Ophthalmology & Visual Science (1 paper)Ophthalmology (1 paper)
- Partner nations
- United States
In The Last Decade
David Coz
5 papers receiving 352 citations
David Coz's Hit Papers
Peers
Comparison fields: 5 of 82
- Health Informatics 82
- Ophthalmology 106
- Health Information Management 43
- Radiology, Nuclear Medicine and Imaging 189
- Artificial Intelligence 127
Countries citing papers authored by David Coz
This map shows the geographic impact of David Coz'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 David Coz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Coz more than expected).
Fields of papers citing papers by David Coz
This network shows the impact of papers produced by David Coz. 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 David Coz. The network helps show where David Coz may publish in the future.
Co-authors
The 25 scholars most cited alongside David Coz, 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 | Using a Deep Learning Algorithm and Integrated Gradients Explanation to Assist Grading for Diabetic Retinopathy Hit paper breakdown → | 2018 | 250 |
| 2 | 2021 | 90 | |
| 3 | DermGAN: Synthetic Generation of Clinical Skin Images with Pathology | 2019 | 12 |
| 4 | 2020 | 8 | |
| 5 | Assisted reads for diabetic retinopathy using a deep learning algorithm and integrated gradient explanation | 2018 | 2 |
About David Coz
David Coz is a scholar working on Artificial Intelligence, Oncology, Radiology, Nuclear Medicine and Imaging, Infectious Diseases and Dermatology, having authored 5 papers that have together received 362 indexed citations. Recurring topics across this work include Cutaneous Melanoma Detection and Management (2 papers), Retinal Imaging and Analysis (2 papers), AI in cancer detection (1 paper), Cell Image Analysis Techniques (1 paper), Artificial Intelligence in Healthcare (1 paper), Retinal Diseases and Treatments (1 paper), Machine Learning and Data Classification (1 paper) and Dermatological diseases and infestations (1 paper). The work is most often cited by research in Health Informatics (82 citations), Ophthalmology (106 citations), Health Information Management (43 citations), Radiology, Nuclear Medicine and Imaging (189 citations) and Artificial Intelligence (127 citations). David Coz has collaborated with scholars based in United States. Frequent co-authors include Lily Peng, Dale R. Webster, Greg S. Corrado, Rory Sayres, Scott Barb, Anthony Joseph, Arunachalam Narayanaswamy, Jonathan Krause, Katy Blumer and Ankur Taly. Their work appears in journals such as JAMA Network Open, Investigative Ophthalmology & Visual Science and Ophthalmology.
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.