Gustav Müller‐Franzes

52 total papers · 1.3k total citations
22 papers, 525 citations indexed

About

Gustav Müller‐Franzes is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Biomedical Engineering. According to data from OpenAlex, Gustav Müller‐Franzes has authored 22 papers receiving a total of 525 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Radiology, Nuclear Medicine and Imaging, 10 papers in Artificial Intelligence and 6 papers in Biomedical Engineering. Recurrent topics in Gustav Müller‐Franzes's work include Radiomics and Machine Learning in Medical Imaging (16 papers), AI in cancer detection (7 papers) and Artificial Intelligence in Healthcare and Education (5 papers). Gustav Müller‐Franzes is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (16 papers), AI in cancer detection (7 papers) and Artificial Intelligence in Healthcare and Education (5 papers). Gustav Müller‐Franzes collaborates with scholars based in Germany, United Kingdom and United States. Gustav Müller‐Franzes's co-authors include Daniel Truhn, Christiane Kühl, Jakob Nikolas Kather, Christoph Haarburger, Sven Nebelung, Firas Khader, Tianyu Han, Soroosh Tayebi Arasteh, Dorit Merhof and Leon Weninger and has published in prestigious journals such as Nature Communications, Scientific Reports and Radiology.

In The Last Decade

Gustav Müller‐Franzes

22 papers receiving 518 citations

Hit Papers

Denoising diffusion proba... 2023 2026 2024 2023 25 50 75 100

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Gustav Müller‐Franzes 300 227 94 81 69 22 525
Avi Ben-Cohen 259 0.9× 203 0.9× 78 0.8× 97 1.2× 115 1.7× 10 581
Katharina Hoebel 233 0.8× 154 0.7× 70 0.7× 44 0.5× 78 1.1× 17 460
Paul Desbordes 285 0.9× 141 0.6× 55 0.6× 40 0.5× 70 1.0× 13 527
Dooman Arefan 413 1.4× 262 1.2× 41 0.4× 40 0.5× 56 0.8× 43 582
Myeongchan Kim 297 1.0× 172 0.8× 124 1.3× 32 0.4× 97 1.4× 13 580
Tianyu Han 231 0.8× 232 1.0× 124 1.3× 95 1.2× 40 0.6× 19 511
Kim Eun Hee 197 0.7× 177 0.8× 43 0.5× 78 1.0× 75 1.1× 25 480
Nathaniel Swinburne 223 0.7× 112 0.5× 106 1.1× 27 0.3× 68 1.0× 18 503
Jianqiao Zhou 353 1.2× 147 0.6× 52 0.6× 38 0.5× 95 1.4× 38 580
Natascha Claudia D’Amico 301 1.0× 195 0.9× 79 0.8× 52 0.6× 98 1.4× 10 528

Countries citing papers authored by Gustav Müller‐Franzes

Since Specialization
Citations

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

Fields of papers citing papers by Gustav Müller‐Franzes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gustav Müller‐Franzes. 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 Gustav Müller‐Franzes. The network helps show where Gustav Müller‐Franzes may publish in the future.

Co-authorship network of co-authors of Gustav Müller‐Franzes

This figure shows the co-authorship network connecting the top 25 collaborators of Gustav Müller‐Franzes. A scholar is included among the top collaborators of Gustav Müller‐Franzes based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Gustav Müller‐Franzes. Gustav Müller‐Franzes is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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