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Explainable deep learning approach to predict chemotherapy effect on breast tumor’s MRI by Mohammed El Adoui; Mohammed Amine Larhmam; Stylianos Drisis; Mohammed Benjelloun is a book available to read on EtoBox.

What is Explainable deep learning approach to predict chemotherapy effect on breast tumor’s MRI about?

Purpose To reduce breast tumor size before surgery, neoadjuvant chemotherapy is applied systematically to patients with local breast cancer. However, with the current protocols, it is not yet workable to have an early prediction on the effect of chemotherapy on a patient. Predicting response to chemotherapy could reduce toxicity and delays to effective treatment. Computational analysis of dynamic contrast-enhanced magnetic resonance images (DCE-MRI) through deep convolution neural network (CNN) has proved a significant performance to classify responsive and nonresponsive patients. This presents a new explainable deep learning (DL) model for predicting breast cancer response to chemotherapy based on multiple MRI inputs. Methods and materials In this study, a cohort of 42 breast cancer patients who underwent chemotherapy was used to train and validate the proposed DL model. This dataset was provided by the Jules Bordet institute of radiology in Brussels, Belgium. A total of 14 external subjects were used to validate the DL model who were classified as responsive or nonresponsive patients based on pre and postchemotherapy DCE-MRI. The model performance was assessed by area under the r

Author

Mohammed El Adoui; Mohammed Amine Larhmam; Stylianos Drisis; Mohammed Benjelloun

Publisher

Elsevier Science & Technology

Published

2023

Language

EN

ISBN

9780128198728