Yannet Interian

624 total citations
16 papers, 334 citations indexed

About

Yannet Interian is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Yannet Interian has authored 16 papers receiving a total of 334 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Radiology, Nuclear Medicine and Imaging, 4 papers in Computer Networks and Communications and 4 papers in Artificial Intelligence. Recurrent topics in Yannet Interian's work include Radiomics and Machine Learning in Medical Imaging (3 papers), Glioma Diagnosis and Treatment (3 papers) and Constraint Satisfaction and Optimization (3 papers). Yannet Interian is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (3 papers), Glioma Diagnosis and Treatment (3 papers) and Constraint Satisfaction and Optimization (3 papers). Yannet Interian collaborates with scholars based in United States, Canada and France. Yannet Interian's 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 and has published in prestigious journals such as International Journal of Radiation Oncology*Biology*Physics, Medical Physics and Radiotherapy and Oncology.

In The Last Decade

Yannet Interian

16 papers receiving 324 citations

Peers

Yannet Interian
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
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Citations per field, relative to Yannet Interian
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Citations per year, relative to Yannet Interian
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Countries citing papers authored by Yannet Interian

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

16 of 16 papers shown
# 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

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.

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2026