Detection and severity quantification of pulmonary embolism with 3D CT data using an automated deep learning-based artificial solution-Reference-Cited by-同舟云学术

Detection and severity quantification of pulmonary embolism with 3D CT data using an automated deep learning-based artificial solution

Published:2023-10 Issue: Volume: Page:
ISSN:2211-5684
Container-title:Diagnostic and Interventional Imaging
language:en
Short-container-title:Diagnostic and Interventional Imaging

Author:

Djahnine Aissam^ORCID,Lazarus Carole,Lederlin Mathieu,Mulé Sébastien^ORCID,Wiemker Rafael^ORCID,Si-Mohamed Salim,Jupin-Delevaux Emilien^ORCID,Nempont Olivier,Skandarani Youssef,De Craene Mathieu,Goubalan Segbedji,Raynaud Caroline,Belkouchi Younes^ORCID,Afia Amira Ben,Fabre Clement,Ferretti Gilbert,De Margerie Constance^ORCID,Berge Pierre^ORCID,Liberge Renan^ORCID,Elbaz Nicolas,Blain Maxime^ORCID,Brillet Pierre-Yves^ORCID,Chassagnon Guillaume,Cadour Farah,Caramella Caroline,Hajjam Mostafa El,Boussouar Samia,Hadchiti Joya^ORCID,Fablet Xavier,Khalil Antoine,Talbot Hugues,Luciani Alain^ORCID,Lassau Nathalie,Boussel Loic

Publisher

Elsevier BV

Subject

Radiology, Nuclear Medicine and imaging,General Medicine,Radiological and Ultrasound Technology

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4. BERT-based natural language processing analysis of French CT reports: application to the measurement of the positivity rate for pulmonary embolism;Jupin-Delevaux;Res Diagn Interv Imaging,2023

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