Pierre Manceron
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
Papers in
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- Occupational and environmental lung diseases 1
- Lung Cancer Diagnosis and Treatment 1
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- Medical Imaging Techniques and Applications 2
- Radiomics and Machine Learning in Medical Imaging 1
- Co-authors
- Andrew G. Nicholson (1 shared paper)Gilles Wainrib (1 shared paper)Nicolas Girard (1 shared paper)Elodie Pronier (1 shared paper)Françoise Galateau-Sallé (1 shared paper)Nolwenn Le Stang (1 shared paper)Thomas Clozel (1 shared paper)Mikhail Zaslavskiy (1 shared paper)
- Journals
- Nature Medicine (1 paper)Journal of Clinical Oncology (1 paper)npj Precision Oncology (1 paper)
- Partner nations
- FranceUnited KingdomUnited States
In The Last Decade
Pierre Manceron
4 papers receiving 328 citations
Pierre Manceron's Hit Papers
Peers
Comparison fields: 5 of 62
- Health Informatics 36
- Radiology, Nuclear Medicine and Imaging 143
- Artificial Intelligence 178
- Biophysics 29
- Cancer Research 47
Countries citing papers authored by Pierre Manceron
This map shows the geographic impact of Pierre Manceron'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 Manceron with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pierre Manceron more than expected).
Fields of papers citing papers by Pierre Manceron
This network shows the impact of papers produced by Pierre Manceron. 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 Manceron. The network helps show where Pierre Manceron may publish in the future.
Co-authors
The 21 scholars most cited alongside Pierre Manceron, 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 | Deep learning-based classification of mesothelioma improves prediction of patient outcome Hit paper breakdown → | 2019 | 326 |
| 2 | 2024 | 2 | |
| 3 | 2025 | 1 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 0 |
About Pierre Manceron
Pierre Manceron is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging, Oncology, Artificial Intelligence and Immunology, having authored 5 papers that have together received 330 indexed citations. Recurring topics across this work include Medical Imaging Techniques and Applications (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Biomarkers in Disease Mechanisms (1 paper), Pancreatic and Hepatic Oncology Research (1 paper), Occupational and environmental lung diseases (1 paper), Human Resource and Talent Management (1 paper), Lung Cancer Diagnosis and Treatment (1 paper) and AI and HR Technologies (1 paper). The work is most often cited by research in Health Informatics (36 citations), Radiology, Nuclear Medicine and Imaging (143 citations), Artificial Intelligence (178 citations), Biophysics (29 citations) and Cancer Research (47 citations). Pierre Manceron has collaborated with scholars based in France, United Kingdom and United States. Frequent co-authors include Andrew G. Nicholson, Gilles Wainrib, Nicolas Girard, Elodie Pronier, Françoise Galateau-Sallé, Nolwenn Le Stang, Thomas Clozel, Mikhail Zaslavskiy, Matahi Moarii and Meriem Sefta. Their work appears in journals such as Nature Medicine, Journal of Clinical Oncology and npj Precision Oncology.
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.