Jan Clusmann

13 papers receiving 530 citations

Hit Papers

Development and validation of an autonomous artificial intelligence agent for clinical decision-making in oncology 2025 · 18 citations
182023202620242025100200300400

Peers

Jan Clusmann
Comparison fields: 5 of 106
  • Health Informatics 299
  • Family Practice 28
  • Health Information Management 39
  • Artificial Intelligence 211
  • Radiology, Nuclear Medicine and Imaging 140
Replace Michaela Unger with:
Michaela Unger Germany
Gregory Patrick Veldhuizen Germany
Hannah Sophie Muti Germany
Sarah Enslin United States
Jan‐Niklas Eckardt Germany
Pranavsingh Dhunnoo Ireland
Supawadee Suppadungsuk Thailand
Luigi De Angelis Italy
Paola Daniore Switzerland
Chiara Maria Lavinia Löffler Germany
Jan Clusmann relative to Michaela Unger Germany Michaela Unger's profile →
Citations per field
00.5×1.5×
Michaela Unger · 1×
Citations per year

Countries citing papers authored by Jan Clusmann

Since Specialization
Citations

This map shows the geographic impact of Jan Clusmann'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 Jan Clusmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jan Clusmann more than expected).

Fields of papers citing papers by Jan Clusmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jan Clusmann. 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 Jan Clusmann. The network helps show where Jan Clusmann may publish in the future.

Co-authors

The 25 scholars most cited alongside Jan Clusmann, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jan Clusmann Line = papers co-authored together Jan Clusmann links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1
The future landscape of large language models in medicine
Hit paper breakdown →
2023472
2
Development and validation of an autonomous artificial intelligence agent for clinical decision-making in oncology
Hit paper breakdown →
202518
3 202211
4 202411
5 20259
6 20247
7 20254
8 20253
9 20253
10 20242
11 20252
12 20232
13 20241
14 20250
15 20250
16 20240
17 20230

About Jan Clusmann

Jan Clusmann is a scholar working on Epidemiology, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Molecular Biology and Health Informatics, having authored 17 papers that have together received 545 indexed citations. Recurring topics across this work include Liver Disease Diagnosis and Treatment (6 papers), Artificial Intelligence in Healthcare and Education (5 papers), Artificial Intelligence in Healthcare (3 papers), Biomedical Text Mining and Ontologies (3 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), COVID-19 diagnosis using AI (2 papers), AI in cancer detection (2 papers) and Liver Diseases and Immunity (2 papers). The work is most often cited by research in Health Informatics (299 citations), Family Practice (28 citations), Health Information Management (39 citations), Artificial Intelligence (211 citations) and Radiology, Nuclear Medicine and Imaging (140 citations). Jan Clusmann has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Jakob Nikolas Kather, Hannah Sophie Muti, Gregory Patrick Veldhuizen, Chiara Maria Lavinia Löffler, Michaela Unger, Narmin Ghaffari Laleh, Jan‐Niklas Eckardt, Sophia J. Wagner, Zunamys I. Carrero and Fiona R. Kolbinger. Their work appears in journals such as Liver International, JHEP Reports, Journal of Hepatology, Cell Death and Disease and Alimentary Pharmacology & Therapeutics.

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.

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