Mikael Lundin
- Oncology top 2%
- Molecular Biology top 5%
- Cancer Research top 2%
- Artificial Intelligence top 1%
- Radiology, Nuclear Medicine and Imaging top 2%
- Co-authors
- Johan LundinJorma IsolaHeikki JoensuuCaj HaglundNina LinderAri RistimäkiStig NordlingTiina Salminen
- Topics
- AI in cancer detection (21 papers)Cell Image Analysis Techniques (11 papers)Radiomics and Machine Learning in Medical Imaging (11 papers)
- Journals
- JAMAThe EMBO JournalPLoS ONE
In The Last Decade
Mikael Lundin
75 papers receiving 4.3k citations
Hit Papers
Peers
Comparison fields: 5 of 170
- Oncology 1.4k
- Molecular Biology 1.3k
- Cancer Research 955
- Artificial Intelligence 869
- Radiology, Nuclear Medicine and Imaging 869
Countries citing papers authored by Mikael Lundin
This map shows the geographic impact of Mikael Lundin'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 Mikael Lundin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mikael Lundin more than expected).
Fields of papers citing papers by Mikael Lundin
This network shows the impact of papers produced by Mikael Lundin. 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 Mikael Lundin. The network helps show where Mikael Lundin may publish in the future.
Co-authorship network of co-authors of Mikael Lundin
This figure shows the co-authorship network connecting the top 25 collaborators of Mikael Lundin. A scholar is included among the top collaborators of Mikael Lundin 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 Mikael Lundin. Mikael Lundin 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 | 9 | |
| 3 | 9 | |
| 4 | 8 | |
| 5 | 53 | |
| 6 | Making use of New Media for pan-European Crisis Communication | 15 |
| 7 | 54 | |
| 8 | 27 | |
| 9 | 181 | |
| 10 | 296 | |
| 11 | 53 | |
| 12 | 31 | |
| 13 | 43 | |
| 14 | 21 | |
| 15 | The MASER-10 microgravity rocket flight | 1 |
| 16 | 159 | |
| 17 | 74 | |
| 18 | 140 | |
| 19 | Amplification of erbB2 and erbB2 expression are superior to estrogen receptor status as risk factors for distant recurrence in pT1N0M0 breast cancer: a nationwide population-based study. | 161 |
| 20 | Short and long term outcome after laparoscopic cholecystectomy. | 8 |
About Mikael Lundin
Mikael Lundin is a scholar working on Biophysics, Cancer Research and Parasitology, having authored 76 papers that have together received 4.4k indexed citations. Recurring topics across this work include AI in cancer detection (21 papers), Cell Image Analysis Techniques (11 papers) and Radiomics and Machine Learning in Medical Imaging (11 papers). The work is most often cited by research in Health Informatics (98 citations), Cancer Research (955 citations) and Oncology (1.4k citations). Mikael Lundin has collaborated with scholars based in Finland, Sweden and Poland. Frequent co-authors include Johan Lundin, Jorma Isola, Heikki Joensuu, Caj Haglund, Nina Linder, Ari Ristimäki, Stig Nordling, Tiina Salminen, Anna Sivula and Riku Turkki. Their work appears in journals such as JAMA, The EMBO Journal and PLoS ONE.
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.