Pierre P. Massion
- Molecular Biology top 1%
- Pulmonary and Respiratory Medicine top 0.5%
- Oncology top 0.5%
- Cancer Research top 0.5%
- Radiology, Nuclear Medicine and Imaging top 1%
- Co-authors
- David P. CarboneRichard M. CaprioliYu ShyrMegan D. HoeksemaAdriana L. GonzalezEric L. GroganPierre ChaurandRosana Eisenberg
- Topics
- Lung Cancer Diagnosis and Treatment (73 papers)Lung Cancer Treatments and Mutations (45 papers)Radiomics and Machine Learning in Medical Imaging (39 papers)
- Partner nations
- United StatesUnited KingdomBelgium
In The Last Decade
Pierre P. Massion
221 papers receiving 10.3k citations
Hit Papers
Peers
Comparison fields: 5 of 160
- Molecular Biology 5.1k
- Pulmonary and Respiratory Medicine 3.8k
- Oncology 3.1k
- Cancer Research 2.1k
- Radiology, Nuclear Medicine and Imaging 1.2k
Countries citing papers authored by Pierre P. Massion
This map shows the geographic impact of Pierre P. Massion'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 Pierre P. Massion with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pierre P. Massion more than expected).
Fields of papers citing papers by Pierre P. Massion
This network shows the impact of papers produced by Pierre P. Massion. 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 Pierre P. Massion. The network helps show where Pierre P. Massion may publish in the future.
Co-authorship network of co-authors of Pierre P. Massion
This figure shows the co-authorship network connecting the top 25 collaborators of Pierre P. Massion. A scholar is included among the top collaborators of Pierre P. Massion 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 Pierre P. Massion. Pierre P. Massion is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 18 | |
| 2 | 11 | |
| 3 | 22 | |
| 4 | 37 | |
| 5 | 29 | |
| 6 | 59 | |
| 7 | 44 | |
| 8 | 43 | |
| 9 | 45 | |
| 10 | 53 | |
| 11 | 45 | |
| 12 | 77 | |
| 13 | 168 | |
| 14 | 283 | |
| 15 | 72 | |
| 16 | 59 | |
| 17 | 115 | |
| 18 | 32 | |
| 19 | 34 | |
| 20 | 110 |
About Pierre P. Massion
Pierre P. Massion is a scholar working on Pulmonary and Respiratory Medicine, Oncology and Cancer Research, having authored 225 papers that have together received 10.4k indexed citations. Recurring topics across this work include Lung Cancer Diagnosis and Treatment (73 papers), Lung Cancer Treatments and Mutations (45 papers) and Radiomics and Machine Learning in Medical Imaging (39 papers). The work is most often cited by research in Cancer Research (2.1k citations), Pulmonary and Respiratory Medicine (3.8k citations) and Oncology (3.1k citations). Pierre P. Massion has collaborated with scholars based in United States, United Kingdom and Belgium. Frequent co-authors include David P. Carbone, Richard M. Caprioli, Yu Shyr, Megan D. Hoeksema, Adriana L. Gonzalez, Eric L. Grogan, Pierre Chaurand, Rosana Eisenberg, Mohamed Hassanein and Heidi Chen. Their work appears in journals such as Proceedings of the National Academy of Sciences, The Lancet and JAMA.
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.