Yannet Interian
- Radiology, Nuclear Medicine and Imaging top 10%
- Radiation top 10%
- Biomedical Engineering
- Sociology and Political Science
- Computer Networks and Communications
- Co-authors
- Mirjam WattenhoferGilmer ValdésTimothy D. SolbergV.C. RideoutEfstathios D. GennatasVasant KearneyOlivier MorinJ Cheung
- Topics
- Radiomics and Machine Learning in Medical Imaging (3 papers)Glioma Diagnosis and Treatment (3 papers)Constraint Satisfaction and Optimization (3 papers)
- Journals
- International Journal of Radiation Oncology*Biology*PhysicsMedical PhysicsRadiotherapy and Oncology
- Partner nations
- United StatesCanadaFrance
In The Last Decade
Yannet Interian
16 papers receiving 324 citations
Peers
Comparison fields: 5 of 68
- Radiology, Nuclear Medicine and Imaging 133
- Radiation 91
- Biomedical Engineering 74
- Sociology and Political Science 63
- Computer Networks and Communications 47
Countries citing papers authored by Yannet Interian
This map shows the geographic impact of Yannet Interian'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 Yannet Interian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yannet Interian more than expected).
Fields of papers citing papers by Yannet Interian
This network shows the impact of papers produced by Yannet Interian. 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 Yannet Interian. The network helps show where Yannet Interian may publish in the future.
Co-authorship network of co-authors of Yannet Interian
This figure shows the co-authorship network connecting the top 25 collaborators of Yannet Interian. A scholar is included among the top collaborators of Yannet Interian based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yannet Interian. Yannet Interian is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 4 | |
| 3 | 1 | |
| 4 | 39 | |
| 5 | 1 | |
| 6 | Training Deep Learning models with small datasets. | 7 |
| 7 | 14 | |
| 8 | 101 | |
| 9 | 68 | |
| 10 | 35 | |
| 11 | 14 | |
| 12 | 5 | |
| 13 | Finding Small Unsatisfiable Cores to Prove Unsatisfiability of QBFs. | 1 |
| 14 | 16 | |
| 15 | A model for generating random quantified boolean formulas | 10 |
| 16 | 14 |
About Yannet Interian
Yannet Interian is a scholar working on Genetics, Radiation and Marketing, having authored 16 papers that have together received 334 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (3 papers), Glioma Diagnosis and Treatment (3 papers) and Constraint Satisfaction and Optimization (3 papers). The work is most often cited by research in Radiation (91 citations), Health Informatics (10 citations) and Radiology, Nuclear Medicine and Imaging (133 citations). Yannet Interian has collaborated with scholars based in United States, Canada and France. Frequent co-authors include Mirjam Wattenhofer, Gilmer Valdés, Timothy D. Solberg, V.C. Rideout, Efstathios D. Gennatas, Vasant Kearney, Olivier Morin, J Cheung, Hubie Chen and Olivier Dubois. Their work appears in journals such as International Journal of Radiation Oncology*Biology*Physics, Medical Physics and Radiotherapy and Oncology.
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.