Stefan Schulz

13 papers receiving 372 citations

Stefan Schulz's Hit Papers

Multistain deep learning for prediction of prognosis and therapy response in colorectal cancer 2023 · 152 citations
1520+1+2Years since publication50100150

Peers

Stefan Schulz
Comparison fields: 5 of 57
  • Health Informatics 25
  • Radiology, Nuclear Medicine and Imaging 127
  • Artificial Intelligence 128
  • Cancer Research 43
  • Oncology 72
Replace Diana Montezuma with:
Diana Montezuma Portugal
Mishka Gidwani United States
Kevin Boehm United States
Peter Truszkowski United States
Nathan Ing United States
Ksenija Kanjer Serbia
Brian Hrycushko United States
Philipp Stenzel Germany
Susanne Melchers Germany
Mostafa Jahanifar United Kingdom
Stefan Schulz relative to Diana Montezuma Portugal Diana Montezuma's profile →
Citations per field
00.5×1.6×
Diana Montezuma · 1×
Citations per year

Countries citing papers authored by Stefan Schulz

Since Specialization
Citations

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

Fields of papers citing papers by Stefan Schulz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Stefan Schulz, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Stefan Schulz Line = papers co-authored together Stefan Schulz links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1
Multistain deep learning for prediction of prognosis and therapy response in colorectal cancer
Hit paper breakdown →
2023152
2 202177
3 202169
4 200925
5 200923
6 200817
7
Determination of the grip force distribution in functional grasping
20044
8 20044
9 20253
10 20063
11 20092
12 20252
13 20231
14
Control of OrtoJacket - an intelligent hybrid orthosis for the paralyzed upper extremity
20111
15 20240
16
Restorative justice - The case for a Child Justice Act.
20090

About Stefan Schulz

Stefan Schulz is a scholar working on Artificial Intelligence, Surgery, Molecular Biology, Radiology, Nuclear Medicine and Imaging and Biomedical Engineering, having authored 16 papers that have together received 383 indexed citations. Recurring topics across this work include AI in cancer detection (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Muscle activation and electromyography studies (3 papers), Biomedical Text Mining and Ontologies (3 papers), Nerve Injury and Rehabilitation (2 papers), Stroke Rehabilitation and Recovery (2 papers), Cancer Genomics and Diagnostics (1 paper) and Criminal Justice and Corrections Analysis (1 paper). The work is most often cited by research in Health Informatics (25 citations), Radiology, Nuclear Medicine and Imaging (127 citations), Artificial Intelligence (128 citations), Cancer Research (43 citations) and Oncology (72 citations). Stefan Schulz has collaborated with scholars based in Germany, Brazil and United Kingdom. Frequent co-authors include Sebastian Foersch, Ann-Christin Woerl, Daniel‐Christoph Wagner, Wilfried Roth, Christina Glasner, Aurélie Fernandez, Markus Eckstein, Arndt Hartmann, Moritz Jesinghaus and Wilko Weichert. Their work appears in journals such as Nature Medicine, Frontiers in Oncology, RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren, Thyroid and Annals of Oncology.

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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