Thomas Ganslandt

106 papers receiving 1.8k citations

Thomas Ganslandt's Hit Papers

Transfer learning for medical image classification: a literature review 2022 · 497 citations
4970+1+2Years since publication100200300400

Peers

Thomas Ganslandt
Comparison fields: 5 of 155
  • Health Information Management 284
  • Health Informatics 75
  • Radiology, Nuclear Medicine and Imaging 227
  • Artificial Intelligence 347
  • Issues, ethics and legal aspects 10
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Guilherme Del Fiol United States
Alex Bui United States
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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 →
2022497
2 2008199
3 201374
4 201560
5 201853
6 200951
7 201141
8 201636
9 201233
10 201031
11 201431
12 201527
13 202125
14 201924
15 201623
16 201223
17 201420
18 201120
19 201819
20 202019

About Thomas Ganslandt

Thomas Ganslandt is a scholar working on Health Information Management, Molecular Biology, Artificial Intelligence, Public Health, Environmental and Occupational Health and Radiology, Nuclear Medicine and Imaging, having authored 109 papers that have together received 1.9k indexed citations. Recurring topics across this work include Electronic Health Records Systems (21 papers), Biomedical Text Mining and Ontologies (18 papers), Semantic Web and Ontologies (8 papers), Scientific Computing and Data Management (8 papers), Clinical practice guidelines implementation (6 papers), Medical and Health Sciences Research (5 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and Data Quality and Management (4 papers). The work is most often cited by research in Health Information Management (284 citations), Health Informatics (75 citations), Radiology, Nuclear Medicine and Imaging (227 citations), Artificial Intelligence (347 citations) and Issues, ethics and legal aspects (10 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, Mahboubeh Jannesari, Nandhini Santhanam, Alejandro Cosa‐Linan, Sebastian Mate, Dennis Toddenroth, Felix Köpcke and Thomas Bürkle. Their work appears in journals such as Methods of Information in Medicine, BMC Medical Informatics and Decision Making, Applied Clinical Informatics, Journal of Medical Internet Research and PLoS ONE.

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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