Daniel P. Noij

697 citations
18 papers · 512 · h-index 14

Impact in

    • Head and Neck Cancer Studies
    • Radiomics and Machine Learning in Medical Imaging
    • MRI in cancer diagnosis
    • Medical Imaging Techniques and Applications
    • Advanced MRI Techniques and Applications
    • Advanced Neuroimaging Techniques and Applications

Papers in

Daniel P. Noij

18 papers receiving 509 citations

Peers

Daniel P. Noij
Comparison fields: 5 of 48
  • Otorhinolaryngology 186
  • Radiology, Nuclear Medicine and Imaging 225
  • Ophthalmology 70
  • Orthopedics and Sports Medicine 20
  • Genetics 20
Replace Roland M. Martens with:
Roland M. Martens Netherlands
Marcus Ruhlmann Germany
Jonathan M. Bernstein United Kingdom
Wojciech Majewski Poland
Thomas Koopman Netherlands
Sara Bartoncini Italy
Tiffany Y. So Hong Kong
Maja Guberina Germany
Walter Choi United States
Kevin Sine United States
Daniel P. Noij relative to Roland M. Martens Netherlands Roland M. Martens's profile →
Citations per field
00.5×10×15×17.5×
Roland M. Martens · 1×
Citations per year

Countries citing papers authored by Daniel P. Noij

Since Specialization
Citations

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

Fields of papers citing papers by Daniel P. Noij

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel P. Noij. 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 Daniel P. Noij. The network helps show where Daniel P. Noij may publish in the future.

Co-authors

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

All Works

18 of 18 papers shown
#Work
1 201462
2 201761
3 201450
4 201940
5 201439
6 201835
7 202033
8 201433
9 202032
10 201826
11 201425
12 201521
13 201416
14 202014
15 202010
16 20189
17 20174
18 20162

About Daniel P. Noij

Daniel P. Noij is a scholar working on Otorhinolaryngology, Radiology, Nuclear Medicine and Imaging, Ophthalmology, Surgery and Genetics, having authored 18 papers that have together received 512 indexed citations. Recurring topics across this work include Head and Neck Cancer Studies (8 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Medical Imaging Techniques and Applications (4 papers), MRI in cancer diagnosis (3 papers), Ocular Oncology and Treatments (2 papers), Advanced MRI Techniques and Applications (2 papers), Cancer Research and Treatments (1 paper) and Cancer, Hypoxia, and Metabolism (1 paper). The work is most often cited by research in Otorhinolaryngology (186 citations), Radiology, Nuclear Medicine and Imaging (225 citations), Ophthalmology (70 citations), Orthopedics and Sports Medicine (20 citations) and Genetics (20 citations). Daniel P. Noij has collaborated with scholars based in Netherlands, Germany and Switzerland. Frequent co-authors include Pim de Graaf, Jonas A. Castelijns, Marcus C. de Jong, Roland M. Martens, C. René Leemans, Remco de Bree, Remco de Bree, J. Tim Marcus, Otto S. Hoekstra and Gerben J.C. Zwezerijnen. Their work appears in journals such as European Journal of Radiology, Oral Oncology, Ophthalmology, European Radiology and Cancers.

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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