Tim Rädsch

886 citations
3 papers · 47 · h-index 2

Impact in

    • Artificial Intelligence in Healthcare and Education
    • Cell Image Analysis Techniques
    • Advanced Fluorescence Microscopy Techniques

Papers in

    • Machine Learning and Data Classification 1
    • AI in cancer detection 1
    • Data Stream Mining Techniques 1
    • Explainable Artificial Intelligence (XAI) 1
    • Anomaly Detection Techniques and Applications 1
    • Artificial Intelligence in Healthcare and Education 2

Tim Rädsch

3 papers receiving 47 citations

Peers

Tim Rädsch
Comparison fields: 5 of 36
  • Health Informatics 8
  • Biophysics 6
  • Artificial Intelligence 22
  • Radiology, Nuclear Medicine and Imaging 12
  • Ecological Modeling 2
Replace Matthias Eisenmann with:
Matthias Eisenmann Germany
Jean-François Rajotte Canada
Julian Viret United States
Luca Lianas Italy
Adam Casson United States
Avinash Kori India
Feidao Cao China
Hagar Hussein Egypt
Matthias Perkonigg Austria
Gianna Tsakou Greece
Tim Rädsch relative to Matthias Eisenmann Germany Matthias Eisenmann's profile →
Citations per field
00.5×1.6×
Matthias Eisenmann · 1×
Citations per year

Countries citing papers authored by Tim Rädsch

Since Specialization
Citations

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

Fields of papers citing papers by Tim Rädsch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 11 scholars most cited alongside Tim Rädsch, 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 Tim Rädsch Line = papers co-authored together Tim Rädsch links everyone, so they are left out of the graph.

All Works

3 of 3 papers shown

About Tim Rädsch

Tim Rädsch is a scholar working on Artificial Intelligence, Health Informatics, Radiology, Nuclear Medicine and Imaging, Infectious Diseases and Organic Chemistry, having authored 3 papers that have together received 47 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Machine Learning and Data Classification (1 paper), AI in cancer detection (1 paper), Data Stream Mining Techniques (1 paper), Explainable Artificial Intelligence (XAI) (1 paper) and Anomaly Detection Techniques and Applications (1 paper). The work is most often cited by research in Health Informatics (8 citations), Biophysics (6 citations), Artificial Intelligence (22 citations), Radiology, Nuclear Medicine and Imaging (12 citations) and Ecological Modeling (2 citations). Tim Rädsch has collaborated with scholars based in Germany and New Zealand. Frequent co-authors include Annika Reinke, Lena Maier‐Hein, Ali Emre Kavur, Nicholas Schreck, Vivienn Weru, Minu D. Tizabi, Tobias Roß, Annette Kopp‐Schneider, Ali Sunyaev and Scott Thiebes. Their work appears in journals such as Journal of the Association for Information Systems and Nature Machine Intelligence.

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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