N. Di Muzio
- Radiation top 0.2%
- Advanced Radiotherapy Techniques 63
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- Prostate Cancer Diagnosis and Treatment 50
- Prostate Cancer Treatment and Research 41
- Radiation Therapy and Dosimetry 12
- Otorhinolaryngology top 1%
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- Medical Imaging Techniques and Applications 32
- Radiomics and Machine Learning in Medical Imaging 23
- Radiation Dose and Imaging 10
- Rheumatology top 5%
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- Pancreatic and Hepatic Oncology Research 9
- Co-authors
- C. FiorinoC. CozzariniR. CalandrinoS. BroggiFerruccio FazioGiovanni Mauro CattaneoFilippo AlongiMaria Picchio
- Partner nations
- ItalyUnited StatesSwitzerland
In The Last Decade
N. Di Muzio
131 papers receiving 3.2k citations
Peers
Comparison fields: 5 of 87
- Radiation 1.5k
- Pulmonary and Respiratory Medicine 2.3k
- Otorhinolaryngology 269
- Radiology, Nuclear Medicine and Imaging 1.2k
- Rheumatology 250
Countries citing papers authored by N. Di Muzio
This map shows the geographic impact of N. Di Muzio'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 N. Di Muzio with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites N. Di Muzio more than expected).
Fields of papers citing papers by N. Di Muzio
This network shows the impact of papers produced by N. Di Muzio. 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 N. Di Muzio. The network helps show where N. Di Muzio may publish in the future.
Co-authorship network
The 25 scholars most cited alongside N. Di Muzio, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 6 | |
| 2 | 2021 | 2 | |
| 3 | 2019 | 1 | |
| 4 | 2018 | 20 | |
| 5 | Early volume variation of positive lymph nodes assessed by in-room MVCT images predicts risk of loco-regional relapses in head and neck cancer patients treated with IMRT | 2015 | 1 |
| 6 | 2015 | 4 | |
| 7 | 2013 | 27 | |
| 8 | 2013 | 42 | |
| 9 | 2013 | 23 | |
| 10 | 2012 | 26 | |
| 11 | 2012 | 21 | |
| 12 | 2011 | 11 | |
| 13 | 2011 | 137 | |
| 14 | 2011 | 20 | |
| 15 | 2011 | 18 | |
| 16 | 2010 | 29 | |
| 17 | 2010 | 65 | |
| 18 | 2009 | 221 | |
| 19 | 2009 | 66 | |
| 20 | 2005 | 2 |
About N. Di Muzio
N. Di Muzio is a scholar working on Radiation, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine, having authored 140 papers that have together received 3.2k indexed citations. Recurring topics across this work include Advanced Radiotherapy Techniques (63 papers), Prostate Cancer Diagnosis and Treatment (50 papers), Prostate Cancer Treatment and Research (41 papers), Medical Imaging Techniques and Applications (32 papers), Radiomics and Machine Learning in Medical Imaging (23 papers), Radiation Therapy and Dosimetry (12 papers), Radiation Dose and Imaging (10 papers) and Pancreatic and Hepatic Oncology Research (9 papers). The work is most often cited by research in Radiation (1.5k citations), Pulmonary and Respiratory Medicine (2.3k citations) and Otorhinolaryngology (269 citations). N. Di Muzio has collaborated with scholars based in Italy, United States and Switzerland. Frequent co-authors include C. Fiorino, C. Cozzarini, R. Calandrino, S. Broggi, Ferruccio Fazio, Giovanni Mauro Cattaneo, Filippo Alongi, Maria Picchio, Francesco Montorsi and Patrizio Rigatti. Their work appears in journals such as Blood, Scientific Reports and The Journal of Urology.
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.