Hugo Le Boité

571 citations
10 papers · 280 indexed · 1 hit paper · h-index 5

Hugo Le Boité

8 papers receiving 277 citations

Hit Papers

A review of deep learning-based information fusion techni...542024202620251020304050

Peers

Hugo Le Boité
Comparison fields: 5 of 65
  • Immunology 155
  • Neurology 20
  • Ophthalmology 21
  • Radiology, Nuclear Medicine and Imaging 49
  • Oncology 58
Replace Gloria Griffante with:
Gloria Griffante Italy
Daniel Rubinstein United States
Michele Bauer United States
Mahmood Khan United Kingdom
Jiehao Zhou United States
Irun R. Cohen Israel
Annie W. Lau-Kilby United States
Erik Slinger Netherlands
Sandrine Buisson France
Laura Johns United States
Hugo Le Boité relative to Gloria Griffante Italy Gloria Griffante's profile →
Citations per field
00.5×4.8×
Gloria Griffante · 1×
Citations per year

Countries citing papers authored by Hugo Le Boité

Since Specialization
Citations

This map shows the geographic impact of Hugo Le Boité'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 Hugo Le Boité with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hugo Le Boité more than expected).

Fields of papers citing papers by Hugo Le Boité

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hugo Le Boité. 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 Hugo Le Boité. The network helps show where Hugo Le Boité may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Hugo Le Boité, 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 Hugo Le Boité Line = papers co-authored together Hugo Le Boité links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1 20250
2 20240
3 20246
4
A review of deep learning-based information fusion techniques for multimodal medical image classificationbreakdown →
202454
5 20241
6 20237
7 20234
8 20231
9 20215
10 2016202

About Hugo Le Boité

Hugo Le Boité is a scholar working on Ophthalmology, Radiology, Nuclear Medicine and Imaging and Health Information Management, having authored 10 papers that have together received 280 indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (7 papers), Retinal Diseases and Treatments (6 papers), Glaucoma and retinal disorders (3 papers), Retinal and Optic Conditions (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Artificial Intelligence in Healthcare (1 paper), interferon and immune responses (1 paper) and Pelvic and Acetabular Injuries (1 paper). The work is most often cited by research in Immunology (155 citations), Neurology (20 citations) and Ophthalmology (21 citations). Hugo Le Boité has collaborated with scholars based in France, United States and Canada. Frequent co-authors include Diane Mathis, Sara Mostafavi, Mark N. Lee, Aviv Regev, Martin Hegen, Devapregasan Moodley, Katherine Rothamel, Jean‐Laurent Casanova, Towfique Raj and Chun Ye. Their work appears in journals such as Computers in Biology and Medicine, PLoS ONE, Translational Vision Science & Technology, Artificial Intelligence in Medicine and Cell.

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.

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