Machine and Deep Learning Prediction Of Prostate Cancer Aggressiveness Using Multiparametric MRI.
Ontology highlight
ABSTRACT: Prostate cancer (PCa) is the most frequent male malignancy and the assessment of PCa aggressiveness, for which a biopsy is required, is fundamental for patient management. Currently, multiparametric (mp) MRI is strongly recommended before biopsy. Quantitative assessment of mpMRI might provide the radiologist with an objective and noninvasive tool for supporting the decision-making in clinical practice and decreasing intra- and inter-reader variability. In this view, high dimensional radiomics features and Machine Learning (ML) techniques, along with Deep Learning (DL) methods working on raw images directly, could assist the radiologist in the clinical workflow. The aim of this study was to develop and validate ML/DL frameworks on mpMRI data to characterize PCas according to their aggressiv
SUBMITTER: Bertelli E
PROVIDER: S-EPMC8792745 | biostudies-literature | 2021
REPOSITORIES: biostudies-literature
ACCESS DATA