Multilingual RECIST classification of radiology reports using supervised learning

OBJECTIVES: The objective of this study is the exploration of Artificial Intelligence and Natural Language Processing techniques to support the automatic assignment of the four Response Evaluation Criteria in Solid Tumors (RECIST) scales based on radiology reports. We also aim at evaluating how lang...

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Detalles Bibliográficos
Autores principales: Mottin, Luc, Goldman, Jean-Philippe, Jäggli, Christoph, Achermann, Rita, Gobeill, Julien, Knafou, Julien, Ehrsam, Julien, Wicky, Alexandre, Gérard, Camille L., Schwenk, Tanja, Charrier, Mélinda, Tsantoulis, Petros, Lovis, Christian, Leichtle, Alexander, Kiessling, Michael K., Michielin, Olivier, Pradervand, Sylvain, Foufi, Vasiliki, Ruch, Patrick
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Digital Health
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10303934/
https://www.ncbi.nlm.nih.gov/pubmed/37388252
http://dx.doi.org/10.3389/fdgth.2023.1195017

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10303934/
https://www.ncbi.nlm.nih.gov/pubmed/37388252
http://dx.doi.org/10.3389/fdgth.2023.1195017

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