Julius Keyl

491 total citations · 1 hit paper
8 papers, 155 citations indexed

About

Julius Keyl is a scholar working on Radiology, Nuclear Medicine and Imaging, Oncology and Artificial Intelligence. According to data from OpenAlex, Julius Keyl has authored 8 papers receiving a total of 155 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Radiology, Nuclear Medicine and Imaging, 4 papers in Oncology and 3 papers in Artificial Intelligence. Recurrent topics in Julius Keyl's work include Radiomics and Machine Learning in Medical Imaging (6 papers), AI in cancer detection (3 papers) and Colorectal Cancer Screening and Detection (2 papers). Julius Keyl is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (6 papers), AI in cancer detection (3 papers) and Colorectal Cancer Screening and Detection (2 papers). Julius Keyl collaborates with scholars based in Germany, Canada and Chile. Julius Keyl's co-authors include Jens Kleesiek, Jan Egger, Jens T. Siveke, Constantin Seibold, Barbara T. Grünwald, Giulia Baldini, Selma Ugurel, David Albers, Martin Schüler and Jürgen Treckmann and has published in prestigious journals such as Annals of Oncology, Medical Image Analysis and European Radiology.

In The Last Decade

Julius Keyl

7 papers receiving 154 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.

CellViT: Vision Transformers for precise cell segmentation and classification

2024 96 citations Constantin Seibold, Julius Keyl et al. Medical Image Analysis profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Julius Keyl Germany	5	76	63	45	34	25	8	155
Dig Vijay Kumar Yarlagadda United States	7	123 1.6×	79 1.3×	54 1.2×	46 1.4×	16 0.6×	9	181
Yunhao Ge United States	10	77 1.0×	53 0.8×	65 1.4×	14 0.4×	11 0.4×	20	184
Aman Rana United States	6	75 1.0×	34 0.5×	35 0.8×	8 0.2×	38 1.5×	16	185
Nawal Houhou Switzerland	7	45 0.6×	58 0.9×	154 3.4×	26 0.8×	11 0.4×	12	238
Xiang‐He Meng China	8	70 0.9×	74 1.2×	15 0.3×	35 1.0×	8 0.3×	19	213
Cristina L. Saratxaga Spain	8	97 1.3×	76 1.2×	52 1.2×	65 1.9×	27 1.1×	13	239
Keluo Yao United States	8	83 1.1×	52 0.8×	13 0.3×	25 0.7×	15 0.6×	14	135
Minu D. Tizabi Germany	7	38 0.5×	79 1.3×	28 0.6×	22 0.6×	18 0.7×	17	203
Brendon Lutnick United States	7	159 2.1×	78 1.2×	85 1.9×	43 1.3×	30 1.2×	18	306
Ronnachai Jaroensri United States	5	200 2.6×	151 2.4×	61 1.4×	57 1.7×	24 1.0×	7	328

Countries citing papers authored by Julius Keyl

Since Specialization

Citations

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

Fields of papers citing papers by Julius Keyl

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Julius Keyl

This figure shows the co-authorship network connecting the top 25 collaborators of Julius Keyl. A scholar is included among the top collaborators of Julius Keyl 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 Julius Keyl. Julius Keyl 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:

8 of 8 papers shown

1.

Keyl, Julius, Andreas Möck, Liliana H. Mochmann, et al.. (2025). Neural interaction explainable AI predicts drug response across cancers. NAR Cancer. 7(3). zcaf029–zcaf029.

2.

Egger, Jan, et al.. (2025). Is DeepSeek-R1 a Game Changer in Healthcare? - A Seed Review. 1 indexed citations

3.

Seibold, Constantin, Julius Keyl, Giulia Baldini, et al.. (2024). CellViT: Vision Transformers for precise cell segmentation and classification. Medical Image Analysis. 94. 103143–103143. 96 indexed citations breakdown →

4.

Seibold, Constantin, Julius Keyl, Saskia Ting, et al.. (2023). Valuing vicinity: Memory attention framework for context-based semantic segmentation in histopathology. Computerized Medical Imaging and Graphics. 107. 102238–102238. 6 indexed citations

5.

Keyl, Julius, Till Plönes, Martin Metzenmacher, et al.. (2023). 1457P Oligometastatic non-small cell lung cancer: Impact of local and systemic treatment approaches on clinical outcome. Annals of Oncology. 34. S828–S828. 1 indexed citations

6.

Keyl, Julius, René Hosch, Simon Bogner, et al.. (2022). Deep learning‐based assessment of body composition and liver tumour burden for survival modelling in advanced colorectal cancer. Journal of Cachexia Sarcopenia and Muscle. 14(1). 545–552. 19 indexed citations

7.

Keyl, Julius, Stefan Kasper, Marcel Wiesweg, et al.. (2022). Multimodal survival prediction in advanced pancreatic cancer using machine learning. ESMO Open. 7(5). 100555–100555. 27 indexed citations

8.

Kim, Moon, Julius Keyl, Jan Egger, et al.. (2022). Deep Learning–driven classification of external DICOM studies for PACS archiving. European Radiology. 32(12). 8769–8776. 5 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.

Explore authors with similar magnitude of impact