Ariana Familiar
- Radiology, Nuclear Medicine and Imaging
- Genetics
- Cognitive Neuroscience
- Neurology
- Biomedical Engineering
- Co-authors
- Won Mok ShimAli NabavizadehAdam ResnickAnahita Fathi KazerooniPhillip B. StormDebanjan HaldarNastaran KhaliliArastoo Vossough
- Topics
- Radiomics and Machine Learning in Medical Imaging (15 papers)Glioma Diagnosis and Treatment (11 papers)Brain Tumor Detection and Classification (6 papers)
- Journals
- Proceedings of the National Academy of SciencesNeurosurgeryAmerican Journal of Neuroradiology
- Partner nations
- United StatesCanadaNetherlands
In The Last Decade
Ariana Familiar
19 papers receiving 147 citations
Peers
Comparison fields: 5 of 46
- Radiology, Nuclear Medicine and Imaging 67
- Genetics 50
- Cognitive Neuroscience 39
- Neurology 21
- Biomedical Engineering 19
Countries citing papers authored by Ariana Familiar
This map shows the geographic impact of Ariana Familiar'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 Ariana Familiar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ariana Familiar more than expected).
Fields of papers citing papers by Ariana Familiar
This network shows the impact of papers produced by Ariana Familiar. 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 Ariana Familiar. The network helps show where Ariana Familiar may publish in the future.
Co-authorship network of co-authors of Ariana Familiar
This figure shows the co-authorship network connecting the top 25 collaborators of Ariana Familiar. A scholar is included among the top collaborators of Ariana Familiar 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 Ariana Familiar. Ariana Familiar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 11 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 0 | |
| 11 | 5 | |
| 12 | 7 | |
| 13 | 0 | |
| 14 | 1 | |
| 15 | 21 | |
| 16 | 1 | |
| 17 | 20 | |
| 18 | Social Value Learning Shifts Conceptual Representations of Faces. | 1 |
| 19 | 4 | |
| 20 | 39 |
About Ariana Familiar
Ariana Familiar is a scholar working on Genetics, Neurology and Radiology, Nuclear Medicine and Imaging, having authored 23 papers that have together received 151 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (15 papers), Glioma Diagnosis and Treatment (11 papers) and Brain Tumor Detection and Classification (6 papers). The work is most often cited by research in Health Informatics (12 citations), Genetics (50 citations) and Radiology, Nuclear Medicine and Imaging (67 citations). Ariana Familiar has collaborated with scholars based in United States, Canada and Netherlands. Frequent co-authors include Won Mok Shim, Ali Nabavizadeh, Adam Resnick, Anahita Fathi Kazerooni, Phillip B. Storm, Debanjan Haldar, Nastaran Khalili, Arastoo Vossough, Sina Bagheri and Hannah Anderson. Their work appears in journals such as Proceedings of the National Academy of Sciences, Neurosurgery and American Journal of Neuroradiology.
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.