Jakob Nikolas Kather
- Artificial Intelligence top 0.2%
- Radiology, Nuclear Medicine and Imaging top 0.2%
- Oncology top 1%
- Health Informatics top 0.01%
- Cancer Research top 1%
- Co-authors
- Narmin Ghaffari LalehNiels HalamaTom LueddeAlexander MarxAlexander T. PearsonDaniel TruhnMichael HoffmeisterHermann Brenner
- Topics
- Radiomics and Machine Learning in Medical Imaging (95 papers)AI in cancer detection (75 papers)Artificial Intelligence in Healthcare and Education (44 papers)
- Partner nations
- GermanyUnited KingdomUnited States
In The Last Decade
Jakob Nikolas Kather
193 papers receiving 7.5k citations
Hit Papers
Peers
Comparison fields: 5 of 197
- Artificial Intelligence 3.3k
- Radiology, Nuclear Medicine and Imaging 3.3k
- Oncology 2.1k
- Health Informatics 1.2k
- Cancer Research 1.1k
Countries citing papers authored by Jakob Nikolas Kather
This map shows the geographic impact of Jakob Nikolas Kather'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 Jakob Nikolas Kather with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jakob Nikolas Kather more than expected).
Fields of papers citing papers by Jakob Nikolas Kather
This network shows the impact of papers produced by Jakob Nikolas Kather. 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 Jakob Nikolas Kather. The network helps show where Jakob Nikolas Kather may publish in the future.
Co-authorship network of co-authors of Jakob Nikolas Kather
This figure shows the co-authorship network connecting the top 25 collaborators of Jakob Nikolas Kather. A scholar is included among the top collaborators of Jakob Nikolas Kather 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 Jakob Nikolas Kather. Jakob Nikolas Kather is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 3 | |
| 4 | 10 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 47 | |
| 9 | 5 | |
| 10 | 11 | |
| 11 | 3 | |
| 12 | GPT-4 for Information Retrieval and Comparison of Medical Oncology Guidelinesbreakdown → | 47 |
| 13 | Denoising diffusion probabilistic models for 3D medical image generationbreakdown → | 121 |
| 14 | 2 | |
| 15 | 8 | |
| 16 | 1 | |
| 17 | 19 | |
| 18 | 69 | |
| 19 | 33 | |
| 20 | 79 |
About Jakob Nikolas Kather
Jakob Nikolas Kather is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence, having authored 214 papers that have together received 7.7k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (95 papers), AI in cancer detection (75 papers) and Artificial Intelligence in Healthcare and Education (44 papers). The work is most often cited by research in Health Informatics (1.2k citations), Radiology, Nuclear Medicine and Imaging (3.3k citations) and Artificial Intelligence (3.3k citations). Jakob Nikolas Kather has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include Narmin Ghaffari Laleh, Niels Halama, Tom Luedde, Alexander Marx, Alexander T. Pearson, Daniel Truhn, Michael Hoffmeister, Hermann Brenner, Cleo‐Aron Weis and Titus J. Brinker. Their work appears in journals such as Nature Medicine, Nature Communications and Journal of Clinical 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.