M. Lamard
Impact in
- Ophthalmology top 2%
- Intraocular Surgery and Lenses
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- Corneal surgery and disorders
Papers in
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- Retinal Imaging and Analysis 7
- COVID-19 diagnosis using AI 3
- Radiomics and Machine Learning in Medical Imaging 2
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- Image Retrieval and Classification Techniques 3
- Advanced Vision and Imaging 3
- Advanced Image and Video Retrieval Techniques 2
- Co-authors
- Béatrice Cochener (10 shared papers)Gwenolé Quellec (11 shared papers)Guy Cazuguel (4 shared papers)C. Roux (1 shared paper)Pierre-Henri Conze (3 shared papers)Gouenou Coatrieux (1 shared paper)Étienne Decencière (1 shared paper)Jing Yan (1 shared paper)
- Journals
- Computers in Biology and Medicine (2 papers)Scientific Reports (1 paper)Medical Image Analysis (1 paper)Journal of Display Technology (1 paper)Journal of Refractive Surgery (1 paper)
- Partner nations
- FranceUnited States
In The Last Decade
M. Lamard
11 papers receiving 339 citations
Peers
Comparison fields: 5 of 42
- Ophthalmology 190
- Radiology, Nuclear Medicine and Imaging 191
- Computer Vision and Pattern Recognition 154
- Epidemiology 177
- Health Informatics 3
Countries citing papers authored by M. Lamard
This map shows the geographic impact of M. Lamard'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 M. Lamard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Lamard more than expected).
Fields of papers citing papers by M. Lamard
This network shows the impact of papers produced by M. Lamard. 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 M. Lamard. The network helps show where M. Lamard may publish in the future.
Co-authors
The 17 scholars most cited alongside M. Lamard, 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 | 2018 | 188 | |
| 2 | 2009 | 137 | |
| 3 | 2011 | 15 | |
| 4 | 2019 | 15 | |
| 5 | 2024 | 8 | |
| 6 | 2012 | 7 | |
| 7 | 2012 | 5 | |
| 8 | 2018 | 3 | |
| 9 | 2012 | 2 | |
| 10 | Contribution Of 3-d Anterior Segment Reconstruction By Rotative Ubm To The Sizing Of Posterior Phakic Iol | 2012 | 1 |
| 11 | 2011 | 1 | |
| 12 | 2024 | 0 | |
| 13 | 2025 | 0 | |
| 14 | 2024 | 0 |
About M. Lamard
M. Lamard is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Ophthalmology, Artificial Intelligence and Surgery, having authored 14 papers that have together received 382 indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (7 papers), COVID-19 diagnosis using AI (3 papers), Image Retrieval and Classification Techniques (3 papers), Advanced Vision and Imaging (3 papers), AI in cancer detection (2 papers), Advanced Image and Video Retrieval Techniques (2 papers), Retinal Diseases and Treatments (2 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). The work is most often cited by research in Ophthalmology (190 citations), Radiology, Nuclear Medicine and Imaging (191 citations), Computer Vision and Pattern Recognition (154 citations), Epidemiology (177 citations) and Health Informatics (3 citations). M. Lamard has collaborated with scholars based in France and United States. Frequent co-authors include Béatrice Cochener, Gwenolé Quellec, Guy Cazuguel, C. Roux, Pierre-Henri Conze, Gouenou Coatrieux, Étienne Decencière, Jing Yan, C. Roux and Ramin Tadayoni. Their work appears in journals such as Computers in Biology and Medicine, Scientific Reports, Medical Image Analysis, Journal of Display Technology and Journal of Refractive Surgery.
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.