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Deep Learning-Driven Radiomic Feature Extraction for Predicting Complete Pathological Response to Neoadjuvant Chemotherapy in Breast Cancer from 18F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography Scans

Title: Deep Learning-Driven Radiomic Feature Extraction for Predicting Complete Pathological Response to Neoadjuvant Chemotherapy in Breast Cancer from 18F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography Scans
Authors: Tareke, Tewele W.; Payan, Neree; Cochet, Alexandre; Arnould, Laurent; Presles, Benoit; Vrigneaud, Jean-Marc; Ghose, Soumya; Meriaudeau, Fabrice; Lalande, Alain
Source: 2025 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Engineering in Medicine and Biology Society (EMBC), 2025 47th Annual International Conference of the IEEE. :1-7 Jul, 2025
Relation: 2025 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Database: IEEE Xplore Digital Library