Katharina Sies

441 total citations
17 papers, 235 citations indexed

About

Katharina Sies is a scholar working on Oncology, Artificial Intelligence and Dermatology. According to data from OpenAlex, Katharina Sies has authored 17 papers receiving a total of 235 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Oncology, 7 papers in Artificial Intelligence and 6 papers in Dermatology. Recurrent topics in Katharina Sies's work include Cutaneous Melanoma Detection and Management (10 papers), AI in cancer detection (7 papers) and Dermatology and Skin Diseases (3 papers). Katharina Sies is often cited by papers focused on Cutaneous Melanoma Detection and Management (10 papers), AI in cancer detection (7 papers) and Dermatology and Skin Diseases (3 papers). Katharina Sies collaborates with scholars based in Germany, Austria and France. Katharina Sies's co-authors include Christine Fink, Holger A. Haenssle, Ferdinand Toberer, Julia K. Winkler, Albert Rosenberger, Alexander Enk, Andreas Blum, Tobias A. Fuchs, Wilhelm Stolz and Christian Ottmann and has published in prestigious journals such as European Journal of Cancer, ChemMedChem and Journal of Dermatological Treatment.

In The Last Decade

Katharina Sies

15 papers receiving 231 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Katharina Sies Germany 8 148 104 56 47 33 17 235
Alex M. Glazer United States 8 184 1.2× 29 0.3× 86 1.5× 72 1.5× 22 0.7× 23 254
Agnessa Gadeliya Goodson United States 6 238 1.6× 39 0.4× 123 2.2× 63 1.3× 47 1.4× 7 378
Alana Durack United Kingdom 5 161 1.1× 44 0.4× 22 0.4× 88 1.9× 22 0.7× 14 228
Joanna Łudzik United States 8 156 1.1× 64 0.6× 15 0.3× 70 1.5× 42 1.3× 24 199
Mohammed Alraddadi Saudi Arabia 2 243 1.6× 174 1.7× 15 0.3× 95 2.0× 17 0.5× 6 330
Koji Horie Japan 10 78 0.5× 51 0.5× 117 2.1× 88 1.9× 6 0.2× 16 333
Serena Magi Italy 12 271 1.8× 32 0.3× 65 1.2× 115 2.4× 41 1.2× 27 411
Mara Cossa Italy 8 124 0.8× 14 0.1× 32 0.6× 75 1.6× 9 0.3× 16 180
Arwa Shana’ah United States 8 53 0.4× 177 1.7× 14 0.3× 33 0.7× 41 1.2× 16 258
Susanne Kimeswenger Austria 7 31 0.2× 23 0.2× 30 0.5× 22 0.5× 5 0.2× 15 131

Countries citing papers authored by Katharina Sies

Since Specialization
Citations

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

Fields of papers citing papers by Katharina Sies

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Katharina Sies

This figure shows the co-authorship network connecting the top 25 collaborators of Katharina Sies. A scholar is included among the top collaborators of Katharina Sies 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 Katharina Sies. Katharina Sies is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
1.
Sies, Katharina, Julia K. Winkler, Christine Fink, et al.. (2022). Does sex matter? Analysis of sex-related differences in the diagnostic performance of a market-approved convolutional neural network for skin cancer detection. European Journal of Cancer. 164. 88–94. 8 indexed citations
2.
3.
Winkler, Julia K., Philipp Tschandl, Ferdinand Toberer, et al.. (2021). Monitoring patients at risk for melanoma: May convolutional neural networks replace the strategy of sequential digital dermoscopy?. European Journal of Cancer. 160. 180–188. 7 indexed citations
4.
Sies, Katharina, Julia K. Winkler, Christine Fink, et al.. (2021). Auswirkungen des „dunklen Rand‐Artefakts“ in dermatoskopischen Bildern auf die diagnostische Leistungsfähigkeit eines deep learning neuronalen Netzwerkes mit Marktzulassung. JDDG Journal der Deutschen Dermatologischen Gesellschaft. 19(6). 842–851.
5.
Winkler, Julia K., Katharina Sies, Christine Fink, et al.. (2021). Collective human intelligence outperforms artificial intelligence in a skin lesion classification task. JDDG Journal der Deutschen Dermatologischen Gesellschaft. 19(8). 1178–1184. 16 indexed citations
6.
Sies, Katharina, Julia K. Winkler, Christine Fink, et al.. (2021). Dark corner artefact and diagnostic performance of a market‐approved neural network for skin cancer classification. JDDG Journal der Deutschen Dermatologischen Gesellschaft. 19(6). 842–850. 12 indexed citations
7.
Sies, Katharina, et al.. (2021). Nailfold videocapillaroscopy identifies microvascular pathologies in psoriasis vulgaris: Results of a prospective controlled study. JDDG Journal der Deutschen Dermatologischen Gesellschaft. 19(12). 1736–1744. 13 indexed citations
8.
Winkler, Julia K., Katharina Sies, Christine Fink, et al.. (2021). Association between different scale bars in dermoscopic images and diagnostic performance of a market-approved deep learning convolutional neural network for melanoma recognition. European Journal of Cancer. 145. 146–154. 18 indexed citations
9.
Winkler, Julia K., Katharina Sies, Christine Fink, et al.. (2021). Kollektive menschliche Intelligenz übertrifft künstliche Intelligenz in einem Quiz zur Klassifizierung von Hautläsionen. JDDG Journal der Deutschen Dermatologischen Gesellschaft. 19(8). 1178–1185. 1 indexed citations
10.
Sies, Katharina, Julia K. Winkler, Michael Zieger, Martin Kaatz, & Holger A. Haenssle. (2020). Neue optische Untersuchungsverfahren für die Diagnostik von Hautkrankheiten. Der Hautarzt. 71(2). 101–108. 1 indexed citations
11.
Sies, Katharina, Julia K. Winkler, Christine Fink, et al.. (2020). Past and present of computer-assisted dermoscopic diagnosis: performance of a conventional image analyser versus a convolutional neural network in a prospective data set of 1,981 skin lesions. European Journal of Cancer. 135. 39–46. 27 indexed citations
12.
Winkler, Julia K., Katharina Sies, Christine Fink, et al.. (2020). Melanoma recognition by a deep learning convolutional neural network—Performance in different melanoma subtypes and localisations. European Journal of Cancer. 127. 21–29. 77 indexed citations
13.
Sies, Katharina & Martin Hartmann. (2020). Neue und wiederentdeckte Pilze. PUBLISSO (German National Library of Medicine). 19(2). 84–87. 1 indexed citations
14.
Sies, Katharina. (2020). Neue und wiederentdeckte Pilze. 36(1). 20–23. 1 indexed citations
15.
Winkler, Julia K., Katharina Sies, Christine Fink, et al.. (2019). Digitalisierte Bildverarbeitung: künstliche Intelligenz im diagnostischen Einsatz. Forum. 35(2). 109–116.
16.
Sies, Katharina & Thomas Ruzicka. (2016). Gefährliche Erbkrankheit blieb jahrelang unerkannt. 64(2). 118–121. 1 indexed citations
17.
Bier, David, Maria Bartel, Katharina Sies, et al.. (2015). Small‐Molecule Stabilization of the 14‐3‐3/Gab2 Protein–Protein Interaction (PPI) Interface. ChemMedChem. 11(8). 911–918. 51 indexed citations

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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