Jesper Molin
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
- Biophysics top 5%
- Cell Image Analysis Techniques
Papers in
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- AI in cancer detection 11
- Intelligent Tutoring Systems and Adaptive Learning 1
-
- Digital Imaging for Blood Diseases 1
- Co-authors
- Claes Lundström (12 shared papers)Sten Thorstenson (1 shared paper)Kalle Åström (1 shared paper)Anders Heyden (1 shared paper)Morten Fjeld (3 shared papers)Horst K. Hahn (2 shared papers)André Homeyer (2 shared papers)Nick Weiss (1 shared paper)
- Journals
- Journal of Pathology Informatics (4 papers)Histopathology (2 papers)Computerized Medical Imaging and Graphics (1 paper)interactions (1 paper)Computer Graphics Forum (1 paper)
- Partner nations
- SwedenGermanyUnited Kingdom
In The Last Decade
Jesper Molin
16 papers receiving 359 citations
Peers
Comparison fields: 5 of 66
- Health Informatics 34
- Biophysics 64
- Artificial Intelligence 267
- Radiology, Nuclear Medicine and Imaging 118
- Computer Vision and Pattern Recognition 73
Countries citing papers authored by Jesper Molin
This map shows the geographic impact of Jesper Molin'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 Jesper Molin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jesper Molin more than expected).
Fields of papers citing papers by Jesper Molin
This network shows the impact of papers produced by Jesper Molin. 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 Jesper Molin. The network helps show where Jesper Molin may publish in the future.
Co-authors
The 16 scholars most cited alongside Jesper Molin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 137 | |
| 2 | 2018 | 59 | |
| 3 | 2016 | 59 | |
| 4 | 2021 | 27 | |
| 5 | 2015 | 21 | |
| 6 | 2018 | 17 | |
| 7 | 2014 | 12 | |
| 8 | 2016 | 9 | |
| 9 | 2017 | 7 | |
| 10 | 2016 | 5 | |
| 11 | 2014 | 5 | |
| 12 | 2021 | 4 | |
| 13 | Verification Staircase: a Design Strategy for Actionable Explanations. | 2020 | 2 |
| 14 | The Importance of UX for Machine Teaching. | 2018 | 2 |
| 15 | 2024 | 2 | |
| 16 | Diagnostic Review with Digital Pathology: Design of digitals tools for routine diagnostic use | 2016 | 2 |
| 17 | 2023 | 1 |
About Jesper Molin
Jesper Molin is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Biophysics, Public Health, Environmental and Occupational Health and Radiology, Nuclear Medicine and Imaging, having authored 17 papers that have together received 371 indexed citations. Recurring topics across this work include AI in cancer detection (11 papers), Cell Image Analysis Techniques (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Digital Imaging in Medicine (2 papers), Intelligent Tutoring Systems and Adaptive Learning (1 paper), Surgical Simulation and Training (1 paper), Gene expression and cancer classification (1 paper) and Digital Imaging for Blood Diseases (1 paper). The work is most often cited by research in Health Informatics (34 citations), Biophysics (64 citations), Artificial Intelligence (267 citations), Radiology, Nuclear Medicine and Imaging (118 citations) and Computer Vision and Pattern Recognition (73 citations). Jesper Molin has collaborated with scholars based in Sweden, Germany and United Kingdom. Frequent co-authors include Claes Lundström, Sten Thorstenson, Kalle Åström, Anders Heyden, Morten Fjeld, Horst K. Hahn, André Homeyer, Nick Weiss, Jonas Löwgren and Darren Treanor. Their work appears in journals such as Journal of Pathology Informatics, Histopathology, Computerized Medical Imaging and Graphics, interactions and Computer Graphics Forum.
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.