Nina A. Mayr
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- Radiomics and Machine Learning in Medical Imaging 44
- MRI in cancer diagnosis 38
- Medical Imaging Techniques and Applications 28
- Radiation top 0.2%
- Advanced Radiotherapy Techniques 76
- Obstetrics and Gynecology top 0.2%
- Endometrial and Cervical Cancer Treatments 50
- Genetics top 1%
- Glioma Diagnosis and Treatment 23
- Pulmonary and Respiratory Medicine top 0.5%
- Brain Metastases and Treatment 25
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- Management of metastatic bone disease 33
- Co-authors
- William T. C. YuhMichael V. KnoppSimon S. LoPaul S. ToftsRuediger E. PortJune S. TaylorJeffrey L. EvelhochElizabeth Henderson
- Partner nations
- United StatesCanadaGermany
In The Last Decade
Nina A. Mayr
216 papers receiving 9.6k citations
Hit Papers
Peers
Comparison fields: 5 of 155
- Radiology, Nuclear Medicine and Imaging 5.3k
- Radiation 1.7k
- Obstetrics and Gynecology 1.5k
- Genetics 953
- Pulmonary and Respiratory Medicine 2.7k
Countries citing papers authored by Nina A. Mayr
This map shows the geographic impact of Nina A. Mayr'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 Nina A. Mayr with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nina A. Mayr more than expected).
Fields of papers citing papers by Nina A. Mayr
This network shows the impact of papers produced by Nina A. Mayr. 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 Nina A. Mayr. The network helps show where Nina A. Mayr may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Nina A. Mayr, 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 | 2024 | 5 | |
| 2 | 2021 | 30 | |
| 3 | 2021 | 46 | |
| 4 | 2021 | 4 | |
| 5 | 2020 | 16 | |
| 6 | 2020 | 7 | |
| 7 | 2020 | 11 | |
| 8 | 2019 | 11 | |
| 9 | 2017 | 87 | |
| 10 | 2012 | 10 | |
| 11 | 2011 | 14 | |
| 12 | 2010 | 94 | |
| 13 | 2009 | 12 | |
| 14 | 2007 | 37 | |
| 15 | 2006 | 20 | |
| 16 | 2002 | 156 | |
| 17 | 1999 | 175 | |
| 18 | 1997 | 91 | |
| 19 | 1995 | 7 | |
| 20 | 1993 | 116 |
About Nina A. Mayr
Nina A. Mayr is a scholar working on Radiation, Obstetrics and Gynecology and Radiology, Nuclear Medicine and Imaging, having authored 224 papers that have together received 9.7k indexed citations. Recurring topics across this work include Advanced Radiotherapy Techniques (76 papers), Endometrial and Cervical Cancer Treatments (50 papers), Radiomics and Machine Learning in Medical Imaging (44 papers), MRI in cancer diagnosis (38 papers), Management of metastatic bone disease (33 papers), Medical Imaging Techniques and Applications (28 papers), Brain Metastases and Treatment (25 papers) and Glioma Diagnosis and Treatment (23 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (5.3k citations), Radiation (1.7k citations) and Obstetrics and Gynecology (1.5k citations). Nina A. Mayr has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include William T. C. Yuh, Michael V. Knopp, Simon S. Lo, Paul S. Tofts, Ruediger E. Port, June S. Taylor, Jeffrey L. Evelhoch, Elizabeth Henderson, Robert M. Weisskoff and Gunnar Brix. Their work appears in journals such as Journal of Clinical Oncology, PLoS ONE and Cancer.
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.