Thomas Clozel
Impact in
- Health Informatics top 2%
-
- Radiomics and Machine Learning in Medical Imaging
Papers in
-
- Epigenetics and DNA Methylation 3
- Glycosylation and Glycoproteins Research 1
- Surgery 4
- Bladder and Urothelial Cancer Treatments 4
- Co-authors
- Gilles Wainrib (7 shared papers)Pierre Courtiol (5 shared papers)Matahi Moarii (5 shared papers)Elodie Pronier (5 shared papers)Mikhail Zaslavskiy (5 shared papers)Olivier Elemento (7 shared papers)Meriem Sefta (3 shared papers)Charlie Saillard (4 shared papers)
- Journals
- Blood (3 papers)Journal of Clinical Oncology (1 paper)Nature Communications (1 paper)Journal of Hepatology (1 paper)Hepatology (1 paper)
- Partner nations
- United StatesFranceCanada
In The Last Decade
Thomas Clozel
17 papers receiving 1.4k citations
Thomas Clozel's Hit Papers
Peers
Comparison fields: 5 of 103
- Health Informatics 72
- Radiology, Nuclear Medicine and Imaging 385
- Biophysics 99
- Cancer Research 205
- Artificial Intelligence 419
Countries citing papers authored by Thomas Clozel
This map shows the geographic impact of Thomas Clozel'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 Thomas Clozel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas Clozel more than expected).
Fields of papers citing papers by Thomas Clozel
This network shows the impact of papers produced by Thomas Clozel. 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 Thomas Clozel. The network helps show where Thomas Clozel may publish in the future.
Co-authors
The 25 scholars most cited alongside Thomas Clozel, 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 | A deep learning model to predict RNA-Seq expression of tumours from whole slide images Hit paper breakdown → | 2020 | 302 |
| 3 | 2020 | 214 | |
| 4 | 2011 | 117 | |
| 5 | 2013 | 115 | |
| 6 | 2014 | 65 | |
| 7 | 2021 | 63 | |
| 8 | 2020 | 50 | |
| 9 | 2016 | 45 | |
| 10 | 2014 | 44 | |
| 11 | 2014 | 29 | |
| 12 | 2012 | 15 | |
| 13 | 2020 | 15 | |
| 14 | 2016 | 11 | |
| 15 | 2023 | 4 | |
| 16 | 2020 | 2 | |
| 17 | 2011 | 1 | |
| 18 | 2013 | 0 |
About Thomas Clozel
Thomas Clozel is a scholar working on Molecular Biology, Surgery, Artificial Intelligence, Pathology and Forensic Medicine and Sociology and Political Science, having authored 18 papers that have together received 1.4k indexed citations. Recurring topics across this work include AI in cancer detection (4 papers), Bladder and Urothelial Cancer Treatments (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Epigenetics and DNA Methylation (3 papers), Lymphoma Diagnosis and Treatment (3 papers), Biomarkers in Disease Mechanisms (1 paper), Pancreatic and Hepatic Oncology Research (1 paper) and Glycosylation and Glycoproteins Research (1 paper). The work is most often cited by research in Health Informatics (72 citations), Radiology, Nuclear Medicine and Imaging (385 citations), Biophysics (99 citations), Cancer Research (205 citations) and Artificial Intelligence (419 citations). Thomas Clozel has collaborated with scholars based in United States, France and Canada. Frequent co-authors include Gilles Wainrib, Pierre Courtiol, Matahi Moarii, Elodie Pronier, Mikhail Zaslavskiy, Olivier Elemento, Meriem Sefta, Charlie Saillard, Benoît Schmauch and Julien Caldéraro. Their work appears in journals such as Blood, Journal of Clinical Oncology, Nature Communications, Journal of Hepatology and Hepatology.
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.