Akshayaa Vaidyanathan
- Radiology, Nuclear Medicine and Imaging top 5%
- Pulmonary and Respiratory Medicine
- Biomedical Engineering
- Artificial Intelligence
- Health Informatics top 2%
- Co-authors
- Philippe LambinRalph T. H. LeijenaarSeán WalshFadila ZerkaWim VosBenjamin MiraglioRoland HustinxJulien Guiot
- Topics
- Radiomics and Machine Learning in Medical Imaging (9 papers)Advanced X-ray and CT Imaging (5 papers)Lung Cancer Diagnosis and Treatment (3 papers)
- Partner nations
- NetherlandsBelgiumUnited States
In The Last Decade
Akshayaa Vaidyanathan
16 papers receiving 466 citations
Hit Papers
Peers
Comparison fields: 5 of 80
- Radiology, Nuclear Medicine and Imaging 268
- Pulmonary and Respiratory Medicine 111
- Biomedical Engineering 84
- Artificial Intelligence 79
- Health Informatics 51
Countries citing papers authored by Akshayaa Vaidyanathan
This map shows the geographic impact of Akshayaa Vaidyanathan'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 Akshayaa Vaidyanathan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Akshayaa Vaidyanathan more than expected).
Fields of papers citing papers by Akshayaa Vaidyanathan
This network shows the impact of papers produced by Akshayaa Vaidyanathan. 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 Akshayaa Vaidyanathan. The network helps show where Akshayaa Vaidyanathan may publish in the future.
Co-authorship network of co-authors of Akshayaa Vaidyanathan
This figure shows the co-authorship network connecting the top 25 collaborators of Akshayaa Vaidyanathan. A scholar is included among the top collaborators of Akshayaa Vaidyanathan 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 Akshayaa Vaidyanathan. Akshayaa Vaidyanathan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 10 | |
| 2 | 11 | |
| 3 | 6 | |
| 4 | 6 | |
| 5 | 0 | |
| 6 | 44 | |
| 7 | 15 | |
| 8 | 26 | |
| 9 | A review in radiomics: Making personalized medicine a reality via routine imagingbreakdown → | 192 |
| 10 | 59 | |
| 11 | 22 | |
| 12 | 1 | |
| 13 | 1 | |
| 14 | 1 | |
| 15 | 61 | |
| 16 | EyeNED workstation: Development of a multi-modal vendor-independent application for annotation, spatial alignment and analysis of retinal images | 4 |
| 17 | 0 | |
| 18 | 13 |
About Akshayaa Vaidyanathan
Akshayaa Vaidyanathan is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Sensory Systems, having authored 18 papers that have together received 472 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (9 papers), Advanced X-ray and CT Imaging (5 papers) and Lung Cancer Diagnosis and Treatment (3 papers). The work is most often cited by research in Health Informatics (51 citations), Radiology, Nuclear Medicine and Imaging (268 citations) and Neurology (51 citations). Akshayaa Vaidyanathan has collaborated with scholars based in Netherlands, Belgium and United States. Frequent co-authors include Philippe Lambin, Ralph T. H. Leijenaar, Seán Walsh, Fadila Zerka, Wim Vos, Benjamin Miraglio, Roland Hustinx, Julien Guiot, Pierre Lovinfosse and Fabio Bottari. Their work appears in journals such as Journal of Clinical Oncology, Journal of Neurophysiology and Scientific Reports.
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.