Key research questions for implementation of artificial intelligence in capsule endoscopy

Background: Artificial intelligence (AI) is rapidly infiltrating multiple areas in medicine, with gastrointestinal endoscopy paving the way in both research and clinical applications. Multiple challenges associated with the incorporation of AI in endoscopy are being addressed in recent consensus doc...

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Autores: Leenhardt, Romain, Koulaouzidis, Anastasios, Histace, Aymeric, Baatrup, Gunnar, Beg, Sabina, Bourreille, Arnaud, de Lange, Thomas, Eliakim, Rami, Iakovidis, Dimitris, Dam Jensen, Michael, Keuchel, Martin, Margalit Yehuda, Reuma, McNamara, Deirdre, Mascarenhas, Miguel, Spada, Cristiano, Seguí Mesquida, Santi, Smedsrud, Pia, Toth, Ervin, Tontini, Gian Eugenio, Klang, Eyal, Dray, Xavier, Kopylov, Uri
Tipo de documento: artigo
Estado:Versão publicada
Data de publicação:2022
País:España
Recursos:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositório:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:2445/194835
Acesso em linha:https://hdl.handle.net/2445/194835
Access Level:Acceso aberto
Palavra-chave:Intel·ligència artificial
Càpsula endoscòpica
Diagnòstic per la imatge
Artificial intelligence
Capsule endoscopy
Diagnostic imaging
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spelling Key research questions for implementation of artificial intelligence in capsule endoscopyLeenhardt, RomainKoulaouzidis, AnastasiosHistace, AymericBaatrup, GunnarBeg, SabinaBourreille, Arnaudde Lange, ThomasEliakim, RamiIakovidis, DimitrisDam Jensen, MichaelKeuchel, MartinMargalit Yehuda, ReumaMcNamara, DeirdreMascarenhas, MiguelSpada, CristianoSeguí Mesquida, SantiSmedsrud, PiaToth, ErvinTontini, Gian EugenioKlang, EyalDray, XavierKopylov, UriIntel·ligència artificialCàpsula endoscòpicaDiagnòstic per la imatgeArtificial intelligenceCapsule endoscopyDiagnostic imagingBackground: Artificial intelligence (AI) is rapidly infiltrating multiple areas in medicine, with gastrointestinal endoscopy paving the way in both research and clinical applications. Multiple challenges associated with the incorporation of AI in endoscopy are being addressed in recent consensus documents. Objectives: In the current paper, we aimed to map future challenges and areas of research for the incorporation of AI in capsule endoscopy (CE) practice. Design: Modified three-round Delphi consensus online survey. Methods: The study design was based on a modified three-round Delphi consensus online survey distributed to a group of CE and AI experts. Round one aimed to map out key research statements and challenges for the implementation of AI in CE. All queries addressing the same questions were merged into a single issue. The second round aimed to rank all generated questions during round one and to identify the top-ranked statements with the highest total score. Finally, the third round aimed to redistribute and rescore the top-ranked statements. Results: Twenty-one (16 gastroenterologists and 5 data scientists) experts participated in the survey. In the first round, 48 statements divided into seven themes were generated. After scoring all statements and rescoring the top 12, the question of AI use for identification and grading of small bowel pathologies was scored the highest (mean score 9.15), correlation of AI and human expert reading-second (9.05), and real-life feasibility-third (9.0). Conclusion: In summary, our current study points out a roadmap for future challenges and research areas on our way to fully incorporating AI in CE reading.SAGE Publications2023202320222023info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://hdl.handle.net/2445/194835Articles publicats en revistes (Matemàtiques i Informàtica)reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésReproducció del document publicat a: https://doi.org/10.1177/17562848221132683Therapeutic Advances in Gastroenterology, 2022, vol. 15https://doi.org/10.1177/17562848221132683cc-by-nc (c) Leenhardt, Romain et al., 2022https://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:2445/1948352026-05-29T05:05:01Z
dc.title.none.fl_str_mv Key research questions for implementation of artificial intelligence in capsule endoscopy
title Key research questions for implementation of artificial intelligence in capsule endoscopy
spellingShingle Key research questions for implementation of artificial intelligence in capsule endoscopy
Leenhardt, Romain
Intel·ligència artificial
Càpsula endoscòpica
Diagnòstic per la imatge
Artificial intelligence
Capsule endoscopy
Diagnostic imaging
title_short Key research questions for implementation of artificial intelligence in capsule endoscopy
title_full Key research questions for implementation of artificial intelligence in capsule endoscopy
title_fullStr Key research questions for implementation of artificial intelligence in capsule endoscopy
title_full_unstemmed Key research questions for implementation of artificial intelligence in capsule endoscopy
title_sort Key research questions for implementation of artificial intelligence in capsule endoscopy
dc.creator.none.fl_str_mv Leenhardt, Romain
Koulaouzidis, Anastasios
Histace, Aymeric
Baatrup, Gunnar
Beg, Sabina
Bourreille, Arnaud
de Lange, Thomas
Eliakim, Rami
Iakovidis, Dimitris
Dam Jensen, Michael
Keuchel, Martin
Margalit Yehuda, Reuma
McNamara, Deirdre
Mascarenhas, Miguel
Spada, Cristiano
Seguí Mesquida, Santi
Smedsrud, Pia
Toth, Ervin
Tontini, Gian Eugenio
Klang, Eyal
Dray, Xavier
Kopylov, Uri
author Leenhardt, Romain
author_facet Leenhardt, Romain
Koulaouzidis, Anastasios
Histace, Aymeric
Baatrup, Gunnar
Beg, Sabina
Bourreille, Arnaud
de Lange, Thomas
Eliakim, Rami
Iakovidis, Dimitris
Dam Jensen, Michael
Keuchel, Martin
Margalit Yehuda, Reuma
McNamara, Deirdre
Mascarenhas, Miguel
Spada, Cristiano
Seguí Mesquida, Santi
Smedsrud, Pia
Toth, Ervin
Tontini, Gian Eugenio
Klang, Eyal
Dray, Xavier
Kopylov, Uri
author_role author
author2 Koulaouzidis, Anastasios
Histace, Aymeric
Baatrup, Gunnar
Beg, Sabina
Bourreille, Arnaud
de Lange, Thomas
Eliakim, Rami
Iakovidis, Dimitris
Dam Jensen, Michael
Keuchel, Martin
Margalit Yehuda, Reuma
McNamara, Deirdre
Mascarenhas, Miguel
Spada, Cristiano
Seguí Mesquida, Santi
Smedsrud, Pia
Toth, Ervin
Tontini, Gian Eugenio
Klang, Eyal
Dray, Xavier
Kopylov, Uri
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Intel·ligència artificial
Càpsula endoscòpica
Diagnòstic per la imatge
Artificial intelligence
Capsule endoscopy
Diagnostic imaging
topic Intel·ligència artificial
Càpsula endoscòpica
Diagnòstic per la imatge
Artificial intelligence
Capsule endoscopy
Diagnostic imaging
description Background: Artificial intelligence (AI) is rapidly infiltrating multiple areas in medicine, with gastrointestinal endoscopy paving the way in both research and clinical applications. Multiple challenges associated with the incorporation of AI in endoscopy are being addressed in recent consensus documents. Objectives: In the current paper, we aimed to map future challenges and areas of research for the incorporation of AI in capsule endoscopy (CE) practice. Design: Modified three-round Delphi consensus online survey. Methods: The study design was based on a modified three-round Delphi consensus online survey distributed to a group of CE and AI experts. Round one aimed to map out key research statements and challenges for the implementation of AI in CE. All queries addressing the same questions were merged into a single issue. The second round aimed to rank all generated questions during round one and to identify the top-ranked statements with the highest total score. Finally, the third round aimed to redistribute and rescore the top-ranked statements. Results: Twenty-one (16 gastroenterologists and 5 data scientists) experts participated in the survey. In the first round, 48 statements divided into seven themes were generated. After scoring all statements and rescoring the top 12, the question of AI use for identification and grading of small bowel pathologies was scored the highest (mean score 9.15), correlation of AI and human expert reading-second (9.05), and real-life feasibility-third (9.0). Conclusion: In summary, our current study points out a roadmap for future challenges and research areas on our way to fully incorporating AI in CE reading.
publishDate 2022
dc.date.none.fl_str_mv 2022
2023
2023
2023
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/194835
url https://hdl.handle.net/2445/194835
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a: https://doi.org/10.1177/17562848221132683
Therapeutic Advances in Gastroenterology, 2022, vol. 15
https://doi.org/10.1177/17562848221132683
dc.rights.none.fl_str_mv cc-by-nc (c) Leenhardt, Romain et al., 2022
https://creativecommons.org/licenses/by-nc/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv cc-by-nc (c) Leenhardt, Romain et al., 2022
https://creativecommons.org/licenses/by-nc/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv SAGE Publications
publisher.none.fl_str_mv SAGE Publications
dc.source.none.fl_str_mv Articles publicats en revistes (Matemàtiques i Informàtica)
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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