Robert Kaczmarczyk

996 total citations
21 papers, 370 citations indexed

About

Robert Kaczmarczyk is a scholar working on Radiology, Nuclear Medicine and Imaging, Dermatology and Health Informatics. According to data from OpenAlex, Robert Kaczmarczyk has authored 21 papers receiving a total of 370 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Radiology, Nuclear Medicine and Imaging, 6 papers in Dermatology and 6 papers in Health Informatics. Recurrent topics in Robert Kaczmarczyk's work include Artificial Intelligence in Healthcare and Education (6 papers), Cutaneous Melanoma Detection and Management (5 papers) and COVID-19 diagnosis using AI (5 papers). Robert Kaczmarczyk is often cited by papers focused on Artificial Intelligence in Healthcare and Education (6 papers), Cutaneous Melanoma Detection and Management (5 papers) and COVID-19 diagnosis using AI (5 papers). Robert Kaczmarczyk collaborates with scholars based in Germany, Sweden and Switzerland. Robert Kaczmarczyk's co-authors include Beatriz Atienza-Carbonell, Lina Mosch, Alexander Zink, Tilo Biedermann, Maximilian Schielein, Tobias Lasser, Anna Balato, Emanuele Scala, Michael Erdmann and Linda Tizek and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Investigative Dermatology and Journal of Medical Internet Research.

In The Last Decade

Robert Kaczmarczyk

19 papers receiving 358 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Robert Kaczmarczyk Germany 7 179 81 80 71 59 21 370
Seyyedeh Fatemeh Mousavi Baigi Iran 11 122 0.7× 47 0.6× 74 0.9× 44 0.6× 80 1.4× 35 371
Robert Ranisch Germany 11 122 0.7× 93 1.1× 40 0.5× 56 0.8× 55 0.9× 37 446
Jenna Lester United States 11 129 0.7× 94 1.2× 39 0.5× 48 0.7× 75 1.3× 34 500
Carl Preiksaitis United States 7 173 1.0× 63 0.8× 65 0.8× 16 0.2× 71 1.2× 25 368
Aanuoluwapo Clement David-Olawade United Kingdom 11 138 0.8× 63 0.8× 85 1.1× 42 0.6× 68 1.2× 33 512
Sahar Borna United States 12 178 1.0× 82 1.0× 59 0.7× 40 0.6× 37 0.6× 47 398
Claudia E. Haupt United States 6 198 1.1× 106 1.3× 76 0.9× 46 0.6× 73 1.2× 24 359
Oliver Maaßen Germany 4 146 0.8× 55 0.7× 53 0.7× 34 0.5× 44 0.7× 5 209
Kay Li Canada 9 288 1.6× 295 3.6× 156 1.9× 82 1.2× 45 0.8× 18 591

Countries citing papers authored by Robert Kaczmarczyk

Since Specialization
Citations

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

Fields of papers citing papers by Robert Kaczmarczyk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Robert Kaczmarczyk

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

All Works

20 of 20 papers shown
1.
2.
Kaczmarczyk, Robert, et al.. (2024). Decoding the Digital Pulse: Bibliometric Analysis of 25 Years in Digital Health Research Through the Journal of Medical Internet Research. Journal of Medical Internet Research. 26. e60057–e60057. 1 indexed citations
3.
Kaczmarczyk, Robert, et al.. (2024). From Language Models to Medical Diagnoses: Assessing the Potential of GPT-4 and GPT-3.5-Turbo in Digital Health. SHILAP Revista de lepidopterología. 5(4). 2680–2692. 3 indexed citations
4.
Kaczmarczyk, Robert, et al.. (2024). Evaluating Bard Gemini Pro and GPT-4 Vision Against Student Performance in Medical Visual Question Answering: Comparative Case Study. JMIR Formative Research. 8. e57592–e57592. 5 indexed citations
5.
Gathen, Martin, et al.. (2024). Does the Information Quality of ChatGPT Meet the Requirements of Orthopedics and Trauma Surgery?. Cureus. 16(5). e60318–e60318. 10 indexed citations
6.
Kaczmarczyk, Robert, et al.. (2024). Evaluating multimodal AI in medical diagnostics. npj Digital Medicine. 7(1). 205–205. 22 indexed citations
7.
Kaczmarczyk, Robert, Tobias Lasser, Tilo Biedermann, Johannes Ring, & Alexander Zink. (2023). Revealing clinically relevant specific IgE sensitization patterns in Hymenoptera venom allergy with dimension reduction and clustering. World Allergy Organization Journal. 16(10). 100820–100820.
8.
Kaczmarczyk, Robert, et al.. (2023). Artificial Intelligence in Medical Education: Comparative Analysis of ChatGPT, Bing, and Medical Students in Germany. JMIR Medical Education. 9. e46482–e46482. 65 indexed citations
9.
Schielein, Maximilian, et al.. (2023). Outlier detection in dermatology: Performance of different convolutional neural networks for binary classification of inflammatory skin diseases. Journal of the European Academy of Dermatology and Venereology. 37(5). 1071–1079. 14 indexed citations
10.
Schielein, Maximilian, et al.. (2023). Automatic body part identification in real‐world clinical dermatological images using machine learning. JDDG Journal der Deutschen Dermatologischen Gesellschaft. 21(8). 863–869. 4 indexed citations
11.
Kaczmarczyk, Robert, et al.. (2023). Large Language Models for Therapy Recommendations Across 3 Clinical Specialties: Comparative Study. Journal of Medical Internet Research. 25. e49324–e49324. 82 indexed citations
12.
Kaczmarczyk, Robert, et al.. (2022). 3-D-Ganzkörperhautscanner – eine neue Ära in Klinik und Forschung?. Die Dermatologie. 73(7). 575–579. 4 indexed citations
13.
Kaczmarczyk, Robert, et al.. (2022). Netzwerkanalysen als nützliche Ergänzung konventioneller Statistik. Die Dermatologie. 73(9). 735–739. 1 indexed citations
14.
Kaczmarczyk, Robert, et al.. (2022). A new way forward? Examining the potential of quantitative analysis of IgE datasets. Allergy Asthma and Clinical Immunology. 18(1). 75–75. 2 indexed citations
15.
Scala, Emanuele, et al.. (2022). Sociodemographic, clinical and therapeutic factors as predictors of life quality impairment in psoriasis: A cross‐sectional study in Italy. Dermatologic Therapy. 35(8). e15622–e15622. 10 indexed citations
16.
Kaczmarczyk, Robert, et al.. (2021). Visualising the past to plan the future: a network analysis of the largest European dermatology conference. European Journal of Dermatology. 31(2). 161–169. 2 indexed citations
17.
Kaczmarczyk, Robert, et al.. (2021). What’s driving dermatology? Contribution title analysis of the largest German Dermatology Congress 2019. Digital Health. 7. 569655850–569655850. 4 indexed citations
18.
Kaczmarczyk, Robert, et al.. (2020). A network analysis of the EADV 2019 conference. Journal of the European Academy of Dermatology and Venereology. 34(12). e820–e822. 1 indexed citations
19.
Kaczmarczyk, Robert, et al.. (2020). Trends and Perspectives for Dermatological Research in Europe: An Abstract Title Analysis of ESDR and IID Congresses 2010–2019. Journal of Investigative Dermatology. 140(9). S197–S200. 6 indexed citations
20.
Kaczmarczyk, Robert, et al.. (2020). Perceptions of Digital Health Education Among European Medical Students: Mixed Methods Survey. Journal of Medical Internet Research. 22(8). e19827–e19827. 130 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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