Daniela Kuhnt

1.1k citations
19 papers · 750 · h-index 13

Impact in

  • Genetics top 5%
    • Glioma Diagnosis and Treatment
    • Advanced Neuroimaging Techniques and Applications
    • Advanced MRI Techniques and Applications
    • Radiomics and Machine Learning in Medical Imaging

Papers in

Daniela Kuhnt

19 papers receiving 729 citations

Peers

Daniela Kuhnt
Comparison fields: 5 of 76
  • Genetics 294
  • Radiology, Nuclear Medicine and Imaging 244
  • Medical Laboratory Technology 16
  • Computational Mathematics 3
  • Neurology 54
Replace C. Trantakis with:
C. Trantakis Germany
Andrea Saladino Italy
Ola M. Rygh Norway
Aage Grønningsaeter Norway
Jianping Dai China
S. Kunze Germany
Vivek Mehta United States
Sarv Priya United States
Fatih Incekara Netherlands
Shanker Raja United States
Daniela Kuhnt relative to C. Trantakis Germany C. Trantakis's profile →
Citations per field
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Citations per year

Countries citing papers authored by Daniela Kuhnt

Since Specialization
Citations

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

Fields of papers citing papers by Daniela Kuhnt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniela Kuhnt, 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 Daniela Kuhnt Line = papers co-authored together Daniela Kuhnt links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 2011248
2 201086
3 201169
4 201269
5 201161
6 201341
7 201037
8 200830
9 201025
10 201024
11 201014
12
Functional imaging: where do we go from here?
201314
13 201313
14 20117
15 20126
16 20123
17 20131
18 20101
19 20111

About Daniela Kuhnt

Daniela Kuhnt is a scholar working on Radiology, Nuclear Medicine and Imaging, Genetics, Cellular and Molecular Neuroscience, Computer Vision and Pattern Recognition and Surgery, having authored 19 papers that have together received 750 indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (10 papers), Advanced Neuroimaging Techniques and Applications (9 papers), Advanced MRI Techniques and Applications (3 papers), Cerebrospinal fluid and hydrocephalus (2 papers), MRI in cancer diagnosis (2 papers), Medical Image Segmentation Techniques (2 papers), Fetal and Pediatric Neurological Disorders (1 paper) and Neurological Complications and Syndromes (1 paper). The work is most often cited by research in Genetics (294 citations), Radiology, Nuclear Medicine and Imaging (244 citations), Medical Laboratory Technology (16 citations), Computational Mathematics (3 citations) and Neurology (54 citations). Daniela Kuhnt has collaborated with scholars based in Germany, Czechia and United States. Frequent co-authors include Christopher Nimsky, M. Bauer, Oliver Ganslandt, Michael Buchfelder, Andreas Becker, Dorit Merhof, Sven-Martin Schlaffer, Bernd Freisleben, Félix Schmid and Alwin E. Goetz. Their work appears in journals such as PLoS ONE, Neurosurgery, Neuro-Oncology, Topics in Magnetic Resonance Imaging and Anesthesia & Analgesia.

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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