Pierre Manceron

568 citations
5 papers · 330 · 1 hit paper · h-index 2

Impact in

Papers in

Pierre Manceron

4 papers receiving 328 citations

Pierre Manceron's Hit Papers

Deep learning-based classification of mesothelioma improves prediction of patient outcome 2019 · 326 citations
3260+2+4Years since publication100200300

Peers

Pierre Manceron
Comparison fields: 5 of 62
  • Health Informatics 36
  • Radiology, Nuclear Medicine and Imaging 143
  • Artificial Intelligence 178
  • Biophysics 29
  • Cancer Research 47
Replace Charles Maussion with:
Charles Maussion France
Ann-Christin Woerl Germany
Aurélie Fernandez Germany
Marko van Treeck Germany
Peter Truszkowski United States
Saba Shafi United States
Tae-Yeong Kwak South Korea
Igor Odintsov United States
Luoting Zhuang United States
Lukas Oldenburg United States
Pierre Manceron relative to Charles Maussion France Charles Maussion's profile →
Citations per field
00.5×1.5×
Charles Maussion · 1×
Citations per year

Countries citing papers authored by Pierre Manceron

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Pierre Manceron Line = papers co-authored together Pierre Manceron links everyone, so they are left out of the graph.

All Works

5 of 5 papers shown
#Work
1
Deep learning-based classification of mesothelioma improves prediction of patient outcome
Hit paper breakdown →
2019326
2 20242
3 20251
4 20241
5 20240

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.

Explore authors with similar magnitude of impact