Sven Stodtmann

24 papers receiving 294 citations

Hit Papers

Practical guide to SHAP analysis: Explaining supervised machine learning model predictions in drug development 2024 · 115 citations
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Peers

Sven Stodtmann
Comparison fields: 5 of 96
  • Health Informatics 11
  • Oncology 63
  • Neurology 30
  • Computational Theory and Mathematics 30
  • Genetics 20
Replace Eugene Jeong with:
Eugene Jeong South Korea
Xinlei Mi United States
Zorayr Manukyan United States
Chengliang Dong United States
Peng‐Chan Lin Taiwan
Alessandra Cianflone Italy
Daniel Backenroth United States
Ibrahim N. Muhsen United States
Zachary E. Brewer United States
Inge Compter Netherlands
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Citations per field
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Citations per year

Countries citing papers authored by Sven Stodtmann

Since Specialization
Citations

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

Fields of papers citing papers by Sven Stodtmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Sven Stodtmann, 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 Sven Stodtmann Line = papers co-authored together Sven Stodtmann links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
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Practical guide to SHAP analysis: Explaining supervised machine learning model predictions in drug development
Hit paper breakdown →
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19 20194
20 201934

About Sven Stodtmann

Sven Stodtmann is a scholar working on Speech and Hearing, Genetics, Rheumatology, Psychiatry and Mental health and Statistics and Probability, having authored 26 papers that have together received 307 indexed citations. Recurring topics across this work include Inflammatory Bowel Disease (8 papers), Microscopic Colitis (7 papers), Biosimilars and Bioanalytical Methods (4 papers), PARP inhibition in cancer therapy (4 papers), DNA Repair Mechanisms (2 papers), Migraine and Headache Studies (2 papers), Machine Learning in Healthcare (2 papers) and Chronic Lymphocytic Leukemia Research (2 papers). The work is most often cited by research in Health Informatics (11 citations), Oncology (63 citations), Neurology (30 citations), Computational Theory and Mathematics (30 citations) and Genetics (20 citations). Sven Stodtmann has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Sven Mensing, Ana Victoria Ponce Bobadilla, Mohamed‐Eslam F. Mohamed, Ahmed Nader, Mohamed I. A. Othman, Matthew Rosebraugh, Maurizio Facheris, Hao Xiong, Rajeev Menon and Silpa Nuthalapati. Their work appears in journals such as The Journal of Clinical Pharmacology, Clinical and Translational Science, Clinical Pharmacology & Therapeutics, Clinical Pharmacokinetics and CPT Pharmacometrics & Systems Pharmacology.

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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