Predicting the Response to FOLFOX-Based Chemotherapy Regimen from Untreated Liver Metastases on Baseline CT: a Deep Neural Network Approach

Ahmad Maaref, Francisco Perdigon Romero, Emmanuel Montagnon, Milena Cerny, Bich Nguyen, Franck Vandenbroucke, Geneviève Soucy, Simon Turcotte, An Tang and Samuel Kadoury

Article (2020)

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Department:	Department of Computer Engineering and Software Engineering
PolyPublie URL:	https://publications.polymtl.ca/45298/
Journal Title:	Journal of Digital Imaging (vol. 33, no. 4)
Publisher:	Springer
DOI:	10.1007/s10278-020-00332-2
Official URL:	https://doi.org/10.1007/s10278-020-00332-2
Date Deposited:	18 Apr 2023 15:01
Last Modified:	25 Sep 2024 16:33

Cite in APA 7:	Maaref, A., Romero, F. P., Montagnon, E., Cerny, M., Nguyen, B., Vandenbroucke, F., Soucy, G., Turcotte, S., Tang, A., & Kadoury, S. (2020). Predicting the Response to FOLFOX-Based Chemotherapy Regimen from Untreated Liver Metastases on Baseline CT: a Deep Neural Network Approach. Journal of Digital Imaging, 33(4), 937-945. https://doi.org/10.1007/s10278-020-00332-2
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