Georg Wölflein

414 total citations · 3 hit papers
10 papers, 155 citations indexed

About

Georg Wölflein is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Cancer Research. According to data from OpenAlex, Georg Wölflein has authored 10 papers receiving a total of 155 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 4 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Cancer Research. Recurrent topics in Georg Wölflein's work include AI in cancer detection (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Cancer Genomics and Diagnostics (3 papers). Georg Wölflein is often cited by papers focused on AI in cancer detection (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Cancer Genomics and Diagnostics (3 papers). Georg Wölflein collaborates with scholars based in United Kingdom, Germany and United States. Georg Wölflein's co-authors include Jakob Nikolas Kather, Daniel Truhn, Dyke Ferber, Isabella C. Wiest, Dirk Jäger, Omar S. M. El Nahhas, Marta Ligero, Christoph Springfeld, Gernot Beutel and Jan‐Niklas Eckardt and has published in prestigious journals such as Nature Communications, Nature Protocols and Cancers.

In The Last Decade

Georg Wölflein

9 papers receiving 155 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

GPT-4 for Information Retrieval and Comparison of Medical Oncology Guidelines

2024 47 citations Dyke Ferber, Isabella C. Wiest et al. NEJM AI profile →
In-context learning enables multimodal large language models to classify cancer pathology images

2024 47 citations Dyke Ferber, Georg Wölflein et al. Nature Communications profile →
Development and validation of an autonomous artificial intelligence agent for clinical decision-making in oncology

2025 18 citations Dyke Ferber, Omar S. M. El Nahhas et al. Nature Cancer profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Georg Wölflein United Kingdom	6	81	52	47	22	19	10	155
Joshua Pantanowitz United States	8	77 1.0×	84 1.6×	67 1.4×	27 1.2×	8 0.4×	17	289
Satvik Tripathi United States	8	86 1.1×	84 1.6×	74 1.6×	29 1.3×	10 0.5×	24	216
Anglin Dent Canada	5	96 1.2×	126 2.4×	104 2.2×	16 0.7×	17 0.9×	6	255
Roman D. Buelow Germany	7	109 1.3×	26 0.5×	85 1.8×	20 0.9×	28 1.5×	8	192
Omar S. M. El Nahhas Germany	7	92 1.1×	25 0.5×	75 1.6×	26 1.2×	31 1.6×	11	177
Maximilian Alber Germany	5	77 1.0×	25 0.5×	52 1.1×	18 0.8×	13 0.7×	13	159
Richard W. Lee United Kingdom	4	89 1.1×	60 1.2×	125 2.7×	16 0.7×	13 0.7×	6	240
Mustafa Nasir-Moin United States	5	63 0.8×	17 0.3×	62 1.3×	12 0.5×	12 0.6×	12	118
Ankush Patel United States	8	181 2.2×	72 1.4×	120 2.6×	39 1.8×	23 1.2×	19	324
Isabella C. Wiest Germany	9	125 1.5×	135 2.6×	73 1.6×	40 1.8×	10 0.5×	23	291

Countries citing papers authored by Georg Wölflein

Since Specialization

Citations

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

Fields of papers citing papers by Georg Wölflein

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Georg Wölflein

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

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

1.

Ferber, Dyke, Omar S. M. El Nahhas, Georg Wölflein, et al.. (2025). Development and validation of an autonomous artificial intelligence agent for clinical decision-making in oncology. Nature Cancer. 6(8). 1337–1349. 18 indexed citations breakdown →

2.

Ligero, Marta, et al.. (2025). Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning. 30807–30817.

3.

Wölflein, Georg, Dyke Ferber, Daniel Truhn, Ognjen Arandjelović, & Jakob Nikolas Kather. (2025). LLM Agents Making Agent Tools. 26092–26130. 1 indexed citations

4.

Ferber, Dyke, Isabella C. Wiest, Georg Wölflein, et al.. (2024). GPT-4 for Information Retrieval and Comparison of Medical Oncology Guidelines. NEJM AI. 1(6). 47 indexed citations breakdown →

5.

Ferber, Dyke, Georg Wölflein, Isabella C. Wiest, et al.. (2024). In-context learning enables multimodal large language models to classify cancer pathology images. Nature Communications. 15(1). 10104–10104. 47 indexed citations breakdown →

6.

Nahhas, Omar S. M. El, Marko van Treeck, Georg Wölflein, et al.. (2024). From whole-slide image to biomarker prediction: end-to-end weakly supervised deep learning in computational pathology. Nature Protocols. 20(1). 293–316. 27 indexed citations

7.

Wölflein, Georg, In Hwa Um, David J. Harrison, & Ognjen Arandjelović. (2023). Whole-Slide Images and Patches of Clear Cell Renal Cell Carcinoma Tissue Sections Counterstained with Hoechst 33342, CD3, and CD8 Using Multiple Immunofluorescence. Data. 8(2). 40–40. 1 indexed citations

8.

Wölflein, Georg, In Hwa Um, David J. Harrison, & Ognjen Arandjelović. (2023). HoechstGAN: Virtual Lymphocyte Staining Using Generative Adversarial Networks. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 4986–4996. 6 indexed citations

9.

Wölflein, Georg, In Hwa Um, Peter D. Caie, et al.. (2022). Use of High-Plex Data Reveals Novel Insights into the Tumour Microenvironment of Clear Cell Renal Cell Carcinoma. Cancers. 14(21). 5387–5387. 7 indexed citations

10.

Arandjelović, Ognjen & Georg Wölflein. (2021). Dataset of Rendered Chess Game State Images. OSF Preprints (OSF Preprints). 1 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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