Thomas Ganslandt

106 papers receiving 1.8k citations

Thomas Ganslandt's Hit Papers

Transfer learning for medical image classification: a literature review 2022 · 442 citations
4420+1+2Years since publication100200300400

Peers

Thomas Ganslandt
Comparison fields: 5 of 158
  • Health Information Management 432
  • Health Informatics 92
  • Artificial Intelligence 462
  • Management Science and Operations Research 178
  • Information Systems and Management 95
Replace Peter R. Rijnbeek with:
Peter R. Rijnbeek Netherlands
Farahnaz Sadoughi Iran
Guilherme Del Fiol United States
Alex Bui United States
Luke V. Rasmussen United States
Taxiarchis Botsis United States
Leila Shahmoradi Iran
Jake Luo United States
Mario Stefanelli Italy
Vojtech Huser United States
Thomas Ganslandt relative to Peter R. Rijnbeek Netherlands Peter R. Rijnbeek's profile →
Citations per field
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Peter R. Rijnbeek · 1×
Citations per year

Countries citing papers authored by Thomas Ganslandt

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Ganslandt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 109 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Transfer learning for medical image classification: a literature review
Hit paper breakdown →
2022442
2 2008199
3 201374
4 201560
5 201853
6 200951
7 201141
8 201636
9 201233
10 201031
11 201430
12 201526
13 201924
14 202122
15 201221
16 201621
17 201120
18 201319
19 199219
20 201419

About Thomas Ganslandt

Thomas Ganslandt is a scholar working on Public Health, Environmental and Occupational Health, Molecular Biology, Health Information Management, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging, having authored 109 papers that have together received 1.8k indexed citations. Recurring topics across this work include Electronic Health Records Systems (28 papers), Biomedical Text Mining and Ontologies (27 papers), Clinical practice guidelines implementation (14 papers), Ethics in Clinical Research (13 papers), Data Quality and Management (12 papers), Scientific Computing and Data Management (12 papers), Semantic Web and Ontologies (10 papers) and Radiomics and Machine Learning in Medical Imaging (8 papers). The work is most often cited by research in Health Information Management (432 citations), Health Informatics (92 citations), Artificial Intelligence (462 citations), Management Science and Operations Research (178 citations) and Information Systems and Management (95 citations). Thomas Ganslandt has collaborated with scholars based in Germany, United Kingdom and Austria. Frequent co-authors include Hans‐Ulrich Prokosch, Kim Eun Hee, Máté E. Maros, Nandhini Santhanam, Mahboubeh Jannesari, Alejandro Cosa‐Linan, Sebastian Mate, Thomas Bürkle, Felix Köpcke and Dennis Toddenroth. Their work appears in journals such as Methods of Information in Medicine, Applied Clinical Informatics, BMC Medical Informatics and Decision Making, Scientific Reports 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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