Kajsa Møllersen
- Radiology, Nuclear Medicine and Imaging top 10%
- Oncology
- Artificial Intelligence top 10%
- Ophthalmology top 5%
- Computer Vision and Pattern Recognition
- Co-authors
- Lars Ailo BongoFred GodtliebsenMaciel ZorteaThomas SchopfStein Olav SkrøvsethSamuel OrtegaLill‐Tove BusundHimar Fabelo
- Topics
- AI in cancer detection (7 papers)Cutaneous Melanoma Detection and Management (6 papers)Radiomics and Machine Learning in Medical Imaging (3 papers)
- Partner nations
- NorwayUnited StatesNetherlands
In The Last Decade
Kajsa Møllersen
19 papers receiving 430 citations
Hit Papers
Peers
Comparison fields: 5 of 127
- Radiology, Nuclear Medicine and Imaging 136
- Oncology 126
- Artificial Intelligence 125
- Ophthalmology 65
- Computer Vision and Pattern Recognition 51
Countries citing papers authored by Kajsa Møllersen
This map shows the geographic impact of Kajsa Møllersen'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 Kajsa Møllersen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kajsa Møllersen more than expected).
Fields of papers citing papers by Kajsa Møllersen
This network shows the impact of papers produced by Kajsa Møllersen. 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 Kajsa Møllersen. The network helps show where Kajsa Møllersen may publish in the future.
Co-authorship network of co-authors of Kajsa Møllersen
This figure shows the co-authorship network connecting the top 25 collaborators of Kajsa Møllersen. A scholar is included among the top collaborators of Kajsa Møllersen 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 Kajsa Møllersen. Kajsa Møllersen 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 | 17 | |
| 3 | 7 | |
| 4 | 2 | |
| 5 | 13 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 4 | |
| 9 | 8 | |
| 10 | 5 | |
| 11 | 2 | |
| 12 | 8 | |
| 13 | 44 | |
| 14 | Reproduction study using public data of: Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographsbreakdown → | 214 |
| 15 | 14 | |
| 16 | 4 | |
| 17 | 10 | |
| 18 | 50 | |
| 19 | 25 | |
| 20 | 13 |
About Kajsa Møllersen
Kajsa Møllersen is a scholar working on Biophysics, Oncology and Artificial Intelligence, having authored 20 papers that have together received 442 indexed citations. Recurring topics across this work include AI in cancer detection (7 papers), Cutaneous Melanoma Detection and Management (6 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). The work is most often cited by research in Ophthalmology (65 citations), Biophysics (40 citations) and Health Information Management (28 citations). Kajsa Møllersen has collaborated with scholars based in Norway, United States and Netherlands. Frequent co-authors include Lars Ailo Bongo, Fred Godtliebsen, Maciel Zortea, Thomas Schopf, Stein Olav Skrøvseth, Samuel Ortega, Lill‐Tove Busund, Himar Fabelo, Gustavo M. Callicó and Jörn Schulz. Their work appears in journals such as Journal of Clinical Oncology, PLoS ONE and PLoS Medicine.
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.