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Congress: ECR25
Poster Number: C-21176
Type: Poster: EPOS Radiologist (scientific)
DOI: 10.26044/ecr2025/C-21176
Authorblock: N-E. Regnard1, S. Charlon2, M. Durteste2, J. Bayet2, J. Ventre2, J-D. Laredo2, A. S. Brendlin3, S. Afat3; 1Lieusaint/FR, 2Paris/FR, 3Tübingen/DE
Disclosures:
Nor-Eddine Regnard: Founder: Gleamer
Stephane Charlon: Consultant: Gleamer
Marion Durteste: Employee: Gleamer
Jules Bayet: Employee: Gleamer
Jeanne Ventre: Employee: Gleamer
Jean-Denis Laredo: Employee: Gleamer
Andreas Stefan Brendlin: Nothing to disclose
Saif Afat: Nothing to disclose
Keywords: Artificial Intelligence, Bones, Oncology, CT, CAD, Diagnostic procedure, Screening, Cancer, Metastases
References

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[9] Ha, Ji Y., Kyung N. Jeon, Kyungsoo Bae, and Bong H. Choi. 2017. ‘Effect of Bone Reading CT Software on Radiologist Performance in Detecting Bone Metastases from Breast Cancer’. The British Journal of Radiology 90 (1072): 20160809. https://doi.org/10.1259/bjr.20160809.

[10] Dembrower, Karin, Alessio Crippa, Eugenia Colón, Martin Eklund, and Fredrik Strand. 2023. ‘Artificial Intelligence for Breast Cancer Detection in Screening Mammography in Sweden: A Prospective, Population-Based, Paired-Reader, Non-Inferiority Study’. The Lancet Digital Health 5 (10): e703–11. https://doi.org/10.1016/S2589-7500(23)00153-X.

[11] Ladbury, Colton, Arya Amini, Ameish Govindarajan, Isa Mambetsariev, Dan J. Raz, Erminia Massarelli, Terence Williams, Andrei Rodin, and Ravi Salgia. 2023. ‘Integration of Artificial Intelligence in Lung Cancer: Rise of the Machine’. Cell Reports Medicine 4 (2): 100933. https://doi.org/10.1016/j.xcrm.2023.100933.

[12] Chmelik, Jiri, Roman Jakubicek, Petr Walek, Jiri Jan, Petr Ourednicek, Lukas Lambert, Elena Amadori, and Giampaolo Gavelli. 2018. ‘Deep Convolutional Neural Network-Based Segmentation and Classification of Difficult to Define Metastatic Spinal Lesions in 3D CT Data’. Medical Image Analysis 49 (October):76–88. https://doi.org/10.1016/j.media.2018.07.008.
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