Radiomics based Machine Learning Models for Classification of Prostate Cancer Grade Groups from Multi Parametric MRI Images
Herein, radiomic models based on preoperative mpMRI and ML were developed to classify prostate cancer into 5 GGs. Our study provides evidence that analysis of quantitative RFs extracted from high b-value DWMRI images based on a combination of FS method RFE and classifier random forest can be applied for multiclass grading of prostate cancer with an accuracy of 97.0%.
Authors
- Mohammad Saied Salehi (ORCID: https://orcid.org/0000-0002-3535-1578)
- Reza Paydar (ORCID: https://orcid.org/0000-0003-4296-1638)
- Asghar Maziar
- Fatemeh Zandie
- Mohammad Reza Bayatiani
Institutions
- Arak University of Medical Sciences (IR)
- Iran University of Medical Sciences (IR)
Publication Details
- Journal
- Journal of Medical Signals & Sensors
- Published
- 2024-12-01
- DOI
- https://doi.org/10.4103/jmss.jmss_47_23
- Citations
- 2
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.81
Funders
- Iran University of Medical Sciences