Aida Laurinavičienė
- Oncology top 10%
- Artificial Intelligence top 5%
- Cancer Research top 10%
- Molecular Biology
- Radiology, Nuclear Medicine and Imaging top 10%
- Co-authors
- Arvydas LaurinavičiusBenoît PlancoulainePaulette HerlinDarius DasevičiusValerijus OstapenkoJustinas BesusparisNicolas ElieSonata Jarmalaitė
- Topics
- AI in cancer detection (12 papers)Breast Cancer Treatment Studies (9 papers)Cell Image Analysis Techniques (7 papers)
- Cited by
- BiophysicsCancer ResearchOncology
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEScientific Reports
- Partner nations
- LithuaniaFranceUnited Kingdom
In The Last Decade
Aida Laurinavičienė
38 papers receiving 783 citations
Peers
Comparison fields: 5 of 106
- Oncology 245
- Artificial Intelligence 218
- Cancer Research 200
- Molecular Biology 190
- Radiology, Nuclear Medicine and Imaging 181
Countries citing papers authored by Aida Laurinavičienė
This map shows the geographic impact of Aida Laurinavičienė'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 Aida Laurinavičienė with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aida Laurinavičienė more than expected).
Fields of papers citing papers by Aida Laurinavičienė
This network shows the impact of papers produced by Aida Laurinavičienė. 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 Aida Laurinavičienė. The network helps show where Aida Laurinavičienė may publish in the future.
Co-authorship network of co-authors of Aida Laurinavičienė
This figure shows the co-authorship network connecting the top 25 collaborators of Aida Laurinavičienė. A scholar is included among the top collaborators of Aida Laurinavičienė 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 Aida Laurinavičienė. Aida Laurinavičienė is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 2 | |
| 3 | 4 | |
| 4 | 5 | |
| 5 | 2 | |
| 6 | 2 | |
| 7 | 9 | |
| 8 | 13 | |
| 9 | 12 | |
| 10 | 17 | |
| 11 | 33 | |
| 12 | 2 | |
| 13 | 121 | |
| 14 | 38 | |
| 15 | 80 | |
| 16 | 6 | |
| 17 | 35 | |
| 18 | 54 | |
| 19 | 15 | |
| 20 | 51 |
About Aida Laurinavičienė
Aida Laurinavičienė is a scholar working on Biophysics, Cancer Research and Oncology, having authored 39 papers that have together received 801 indexed citations. Recurring topics across this work include AI in cancer detection (12 papers), Breast Cancer Treatment Studies (9 papers) and Cell Image Analysis Techniques (7 papers). The work is most often cited by research in Biophysics (89 citations), Cancer Research (200 citations) and Oncology (245 citations). Aida Laurinavičienė has collaborated with scholars based in Lithuania, France and United Kingdom. Frequent co-authors include Arvydas Laurinavičius, Benoît Plancoulaine, Paulette Herlin, Darius Dasevičius, Valerijus Ostapenko, Justinas Besusparis, Nicolas Elie, Sonata Jarmalaitė, Raimundas Meškauskas and Allan G. Rasmusson. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE 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.