Michaela Kargl

478 citations
8 papers · 227 · h-index 5

Impact in

    • Artificial Intelligence in Healthcare and Education
    • Explainable Artificial Intelligence (XAI)
    • AI in cancer detection
    • Machine Learning in Healthcare

Papers in

Michaela Kargl

7 papers receiving 223 citations

Peers

Michaela Kargl
Comparison fields: 5 of 65
  • Health Informatics 72
  • Artificial Intelligence 133
  • Human-Computer Interaction 16
  • Safety Research 19
  • Radiology, Nuclear Medicine and Imaging 44
Replace Thomas Hartvigsen with:
Thomas Hartvigsen United States
Wiard Jorritsma Netherlands
Jérémie Clos United Kingdom
Andrés Páez Colombia
Roger Schaer Switzerland
David Schneeberger Austria
Tjeerd Schoonderwoerd Netherlands
Alina Jade Barnett United States
Yining Mao China
A Subaveerapandiyan India
Michaela Kargl relative to Thomas Hartvigsen United States Thomas Hartvigsen's profile →
Citations per field
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Thomas Hartvigsen · 1×
Citations per year

Countries citing papers authored by Michaela Kargl

Since Specialization
Citations

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

Fields of papers citing papers by Michaela Kargl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside Michaela Kargl, 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 Michaela Kargl Line = papers co-authored together Michaela Kargl links everyone, so they are left out of the graph.

All Works

8 of 8 papers shown
#Work
1 202286
2 202256
3 202353
4 202215
5 202210
6 20194
7 20253
8 20260

About Michaela Kargl

Michaela Kargl is a scholar working on Artificial Intelligence, Health Informatics, Molecular Biology, Computer Vision and Pattern Recognition and Biophysics, having authored 8 papers that have together received 227 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (3 papers), AI in cancer detection (3 papers), Biomedical Text Mining and Ontologies (2 papers), Explainable Artificial Intelligence (XAI) (2 papers), Digital Imaging for Blood Diseases (1 paper), Persona Design and Applications (1 paper), Innovative Human-Technology Interaction (1 paper) and Technology Use by Older Adults (1 paper). The work is most often cited by research in Health Informatics (72 citations), Artificial Intelligence (133 citations), Human-Computer Interaction (16 citations), Safety Research (19 citations) and Radiology, Nuclear Medicine and Imaging (44 citations). Michaela Kargl has collaborated with scholars based in Austria, Germany and Slovenia. Frequent co-authors include Heimo Müller, Markus Plass, Andreas Holzinger, Christian Geißler, Norman Zerbe, Tim‐Rasmus Kiehl, Peter Regitnig, Carl Orge Retzlaff, Rita Carvalho and Robert Reihs. Their work appears in journals such as Future Generation Computer Systems, Artificial Intelligence in Medicine, IEEE Computer Graphics and Applications, The Journal of Pathology Clinical Research and IEEE Access.

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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