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Posts
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Blog Post number 4
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Blog Post number 1
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publications
MRI-Based Surrogate Imaging Markers of Aggressiveness in Prostate Cancer: Development of a Machine Learning Model Based on Radiomic Features
Published in Mdpi Diagnostics, 2022
This study aimed to develop a noninvasive Machine Learning (ML) model to identify clinically significant prostate cancer (csPCa) according to Gleason Score (GS) based on biparametric MRI (bpMRI) radiomic features and clinical information.
Recommended citation: Dominguez, I., Rios-Ibacache, O., Caprile, P., Gonzalez, J., San Francisco, I. F., & Besa, C. (2023). MRI-Based Surrogate Imaging Markers of Aggressiveness in Prostate Cancer: Development of a Machine Learning Model Based on Radiomic Features. Diagnostics, 13(17), 2779. https://doi.org/10.3390/diagnostics13172779
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talks
Development of an MRI radiomic-based ML model to predict the aggressiveness of prostate cancer
Published:
Rios-Ibacache, O. et al. (2022)
Development and evaluation of a novel artificial intelligence model to predict radiotherapy replanning for head and neck cancer
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Rios-Ibacache, O. et al. (2023)
Development and evaluation of a novel artificial intelligence model to predict radiotherapy replanning for head and neck cancer
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Rios-Ibacache, O. et al. (2023)
Development and evaluation of a novel artificial intelligence model to predict radiotherapy replanning for head and neck cancer
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Rios-Ibacache, O., et al. (2024)
Development and evaluation of novel parameters for describing anatomical changes and predicting radiotherapy replanning for head and neck cancer patients
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Rios-Ibacache, O. et al. (2024)
Development of geometrical parameters for characterizing anatomical alterations in head and neck cancer patients and evaluating radiotherapy replannin
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Rios-Ibacache, O. et al. (2024)
Development and evaluation of novel parameters for describing anatomi cal changes and predicting radiotherapy replanning for head and neck cancer patients
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Rios-Ibacache, O. et al. (2024)
Towards the quantification of anatomical changes in head and neck cancer patients
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Rios-Ibacache, O. et al. (2024). (description)