Michaela Kargl

438 citations
8 papers · 200 indexed · 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 193 citations

Peers

Michaela Kargl
Comparison fields: 5 of 67
  • Health Informatics 74
  • Artificial Intelligence 131
  • Human-Computer Interaction 16
  • Safety Research 19
  • Family Practice 5
Replace Wiard Jorritsma with:
Wiard Jorritsma Netherlands
Mara Graziani Switzerland
David Schneeberger Austria
Andrés Páez Colombia
Roger Schaer Switzerland
Lorenz Kuhn Switzerland
Heliodoro Tejeda United States
Yining Mao China
Mert Yüksekgönül United States
Yifan Yang United States
Michaela Kargl relative to Wiard Jorritsma Netherlands Wiard Jorritsma's profile →
Citations per field
00.5×1.5×2.4×
Wiard Jorritsma · 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-authorship network

The 21 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 20260
2 20253
3 202345
4 20229
5 202278
6 202213
7 202248
8 20194

About Michaela Kargl

Michaela Kargl is a scholar working on Health Informatics, Human-Computer Interaction, Biophysics, Artificial Intelligence and Safety Research, having authored 8 papers that have together received 200 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), Radiomics and Machine Learning in Medical Imaging (1 paper), Ethics in Clinical Research (1 paper), Persona Design and Applications (1 paper) and Machine Learning in Healthcare (1 paper). The work is most often cited by research in Health Informatics (74 citations), Artificial Intelligence (131 citations), Human-Computer Interaction (16 citations), Safety Research (19 citations) and Family Practice (5 citations). Michaela Kargl has collaborated with scholars based in Austria, Germany and Slovenia. Frequent co-authors include Heimo Müller, Markus Plass, Andreas Holzinger, Norman Zerbe, Christian Geißler, Tim‐Rasmus Kiehl, Peter Regitnig, Carl Orge Retzlaff, Robert Reihs and Kurt Zatloukal. Their work appears in journals such as Artificial Intelligence in Medicine, Histopathology, IEEE Access, IEEE Computer Graphics and Applications and Yearbook of Medical Informatics.

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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