Marc Coram
- Health Informatics top 0.05%
- Ophthalmology top 0.2%
- Retinal Diseases and Treatments 2
- Health Information Management top 0.1%
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- Retinal Imaging and Analysis 2
- Artificial Intelligence top 1%
- Bayesian Methods and Mixture Models 2
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- Genetic Associations and Epidemiology 6
- Genetic and phenotypic traits in livestock 6
- Genetic Mapping and Diversity in Plants and Animals 4
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- Metabolomics and Mass Spectrometry Studies 3
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- Mass Spectrometry Techniques and Applications 3
- Co-authors
- Dale R. WebsterDerek WuKim RamasamyVarun GulshanRajiv RamanKasumi WidnerLily PengSubhashini Venugopalan
- Partner nations
- United StatesIndiaSouth Africa
In The Last Decade
Marc Coram
29 papers receiving 5.9k citations
Hit Papers
Peers
Comparison fields: 5 of 196
- Health Informatics 648
- Ophthalmology 1.6k
- Health Information Management 601
- Radiology, Nuclear Medicine and Imaging 2.9k
- Artificial Intelligence 1.2k
Countries citing papers authored by Marc Coram
This map shows the geographic impact of Marc Coram'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 Marc Coram with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marc Coram more than expected).
Fields of papers citing papers by Marc Coram
This network shows the impact of papers produced by Marc Coram. 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 Marc Coram. The network helps show where Marc Coram may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Marc Coram, 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 | 2021 | 5 | |
| 2 | 2020 | 40 | |
| 3 | 2017 | 55 | |
| 4 | Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographsbreakdown → | 2016 | 4490 |
| 5 | 2015 | 18 | |
| 6 | 2014 | 3 | |
| 7 | 2013 | 93 | |
| 8 | 2013 | 96 | |
| 9 | 2012 | 8 | |
| 10 | 2011 | 86 | |
| 11 | 2008 | 82 | |
| 12 | 2008 | 49 | |
| 13 | 2008 | 173 | |
| 14 | 2007 | 3 | |
| 15 | 2007 | 2 | |
| 16 | 2007 | 1 | |
| 17 | 2006 | 47 | |
| 18 | 2006 | 193 | |
| 19 | 2006 | 92 | |
| 20 | Nonparametric bayesian classification | 2002 | 1 |
About Marc Coram
Marc Coram is a scholar working on Transplantation, Genetics, Hematology, Statistics and Probability and Algebra and Number Theory, having authored 30 papers that have together received 6.2k indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (6 papers), Genetic and phenotypic traits in livestock (6 papers), Genetic Mapping and Diversity in Plants and Animals (4 papers), Metabolomics and Mass Spectrometry Studies (3 papers), Mass Spectrometry Techniques and Applications (3 papers), Bayesian Methods and Mixture Models (2 papers), Retinal Diseases and Treatments (2 papers) and Retinal Imaging and Analysis (2 papers). The work is most often cited by research in Health Informatics (648 citations), Ophthalmology (1.6k citations), Health Information Management (601 citations), Radiology, Nuclear Medicine and Imaging (2.9k citations) and Artificial Intelligence (1.2k citations). Marc Coram has collaborated with scholars based in United States, India and South Africa. Frequent co-authors include Dale R. Webster, Derek Wu, Kim Ramasamy, Varun Gulshan, Rajiv Raman, Kasumi Widner, Lily Peng, Subhashini Venugopalan, Arunachalam Narayanaswamy and Jorge Cuadros. Their work appears in journals such as The American Journal of Human Genetics, Blood, PLoS Genetics, The Journal of Urology and JAMA.
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.