Florian Soudan

698 total citations · 1 hit paper
5 papers, 473 citations indexed

About

Florian Soudan is a scholar working on Oncology, Surgery and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Florian Soudan has authored 5 papers receiving a total of 473 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Oncology, 2 papers in Surgery and 1 paper in Pulmonary and Respiratory Medicine. Recurrent topics in Florian Soudan's work include Colorectal Cancer Screening and Detection (5 papers), Radiomics and Machine Learning in Medical Imaging (1 paper) and Helicobacter pylori-related gastroenterology studies (1 paper). Florian Soudan is often cited by papers focused on Colorectal Cancer Screening and Detection (5 papers), Radiomics and Machine Learning in Medical Imaging (1 paper) and Helicobacter pylori-related gastroenterology studies (1 paper). Florian Soudan collaborates with scholars based in Canada, United States and India. Florian Soudan's co-authors include Michael F. Byrne, Nadeem Iqbal, Florent Chandelier, Nicolas Chapados, Raymond Kelly, Douglas K. Rex, James E. East, Remo Panaccione, Marietta Iacucci and Sameer Berry and has published in prestigious journals such as Gut, Gastrointestinal Endoscopy and Journal of Crohn s and Colitis.

In The Last Decade

Florian Soudan

5 papers receiving 457 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Real-time differentiation of adenomatous and hyperplastic diminutive colorectal polyps during analysis of unaltered videos of standard colonoscopy using a deep learning model

2017 423 citations Michael F. Byrne, Nicolas Chapados et al. Gut profile →

Peers

Countries citing papers authored by Florian Soudan

Since Specialization

Citations

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

Fields of papers citing papers by Florian Soudan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Florian Soudan. 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 Florian Soudan. The network helps show where Florian Soudan may publish in the future.

Co-authorship network of co-authors of Florian Soudan

This figure shows the co-authorship network connecting the top 25 collaborators of Florian Soudan. A scholar is included among the top collaborators of Florian Soudan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Florian Soudan. Florian Soudan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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5 of 5 papers shown

#	Work	Indexed citations
1	Application of Deep Learning Models to Improve Ulcerative Colitis Endoscopic Disease Activity Scoring Under Multiple Scoring Systems 2022 ·Journal of Crohn s and Colitis ·Michael F. Byrne, Remo Panaccione, James E. East, Marietta Iacucci, Nasim Parsa, Rakesh Kalapala, D. Nageshwar Reddy, (unknown), (unknown), Sameer Berry, (unknown), Florian Soudan, (unknown), (unknown), (unknown), Paul Lemaître, (unknown), (unknown), (unknown), Simon Travis	33
2	DOP13 Artificial Intelligence (AI) in endoscopy - Deep learning for detection and scoring of Ulcerative Colitis (UC) disease activity under multiple scoring systems 2021 ·Journal of Crohn s and Colitis ·Michelle L. Byrne, James E. East, Marietta Iacucci, Remo Panaccione, Rakesh Kalapala, (unknown), (unknown), Anita Singh, (unknown), Sameer Berry, (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), Florian Soudan, Simon Travis	5
3	Mo1679 REAL-TIME ARTIFICIAL INTELLIGENCE “FULL COLONOSCOPY WORKFLOW” FOR AUTOMATIC DETECTION FOLLOWED BY OPTICAL BIOPSY OF COLORECTAL POLYPS 2018 ·Gastrointestinal Endoscopy ·Michael F. Byrne, Florian Soudan, (unknown), (unknown), Nicolas Chapados, (unknown), (unknown), Nicolas Guizard, (unknown), (unknown), Andrew Sullivan, Florent Chandelier, Douglas K. Rex	3
4	Real-time differentiation of adenomatous and hyperplastic diminutive colorectal polyps during analysis of unaltered videos of standard colonoscopy using a deep learning model breakdown → 2017 ·Gut ·Michael F. Byrne, Nicolas Chapados, Florian Soudan, (unknown), (unknown), Raymond Kelly, Nadeem Iqbal, Florent Chandelier, Douglas K. Rex	423
5	Su1614 Artificial Intelligence (AI) in Endoscopy--Deep Learning for Optical Biopsy of Colorectal Polyps in Real-Time on Unaltered Endoscopic Videos 2017 ·Gastrointestinal Endoscopy ·Michael F. Byrne, Nicolas Chapados, Florian Soudan, (unknown), (unknown), Raymond Kelly, Nadeem Iqbal, Florent Chandelier, Douglas K. Rex	9

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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