Paul Hérent
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis
- COVID-19 diagnosis using AI
Papers in
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- Radiomics and Machine Learning in Medical Imaging 3
- Medical Imaging Techniques and Applications 1
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- Lung Cancer Diagnosis and Treatment 1
- Co-authors
- Paul Jehanno (3 shared papers)Simon Jégou (3 shared papers)Charlie Saillard (2 shared papers)Benoît Schmauch (2 shared papers)Olivier Dehaene (2 shared papers)Nathalie Lassau (2 shared papers)Alain Luciani (2 shared papers)Christophe Aubé (1 shared paper)
- Journals
- Diagnostic and Interventional Imaging (3 papers)Arthritis Research & Therapy (1 paper)Developmental Cognitive Neuroscience (1 paper)Imagerie de la Femme (1 paper)
- Partner nations
- France
In The Last Decade
Paul Hérent
6 papers receiving 306 citations
Peers
Comparison fields: 5 of 59
- Health Informatics 32
- Radiology, Nuclear Medicine and Imaging 187
- Hepatology 51
- Health Information Management 17
- Artificial Intelligence 108
Countries citing papers authored by Paul Hérent
This map shows the geographic impact of Paul Hérent'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 Paul Hérent with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paul Hérent more than expected).
Fields of papers citing papers by Paul Hérent
This network shows the impact of papers produced by Paul Hérent. 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 Paul Hérent. The network helps show where Paul Hérent may publish in the future.
Co-authors
The 25 scholars most cited alongside Paul Hérent, 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 | 2019 | 115 | |
| 2 | 2019 | 82 | |
| 3 | 2021 | 57 | |
| 4 | 2020 | 40 | |
| 5 | 2019 | 21 | |
| 6 | 2019 | 1 |
About Paul Hérent
Paul Hérent is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Geriatrics and Gerontology, Cognitive Neuroscience and Health Informatics, having authored 6 papers that have together received 316 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (3 papers), Lung Cancer Diagnosis and Treatment (1 paper), Body Composition Measurement Techniques (1 paper), Medical Imaging Techniques and Applications (1 paper), EEG and Brain-Computer Interfaces (1 paper), Osteoarthritis Treatment and Mechanisms (1 paper), Rheumatoid Arthritis Research and Therapies (1 paper) and Artificial Intelligence in Healthcare and Education (1 paper). The work is most often cited by research in Health Informatics (32 citations), Radiology, Nuclear Medicine and Imaging (187 citations), Hepatology (51 citations), Health Information Management (17 citations) and Artificial Intelligence (108 citations). Paul Hérent has collaborated with scholars based in France. Frequent co-authors include Paul Jehanno, Simon Jégou, Charlie Saillard, Benoît Schmauch, Olivier Dehaene, Nathalie Lassau, Alain Luciani, Christophe Aubé, Julia Arfi‐Rouche and Corinne Balleyguier. Their work appears in journals such as Diagnostic and Interventional Imaging, Arthritis Research & Therapy, Developmental Cognitive Neuroscience and Imagerie de la Femme.
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.