Radiomics based Machine Learning Models for Classification of Prostate Cancer Grade Groups from Multi Parametric MRI Images

Purpose: This study aimed to investigate the performance of multiparametric magnetic resonance imaging (mpMRI) radiomic feature-based machine learning (ML) models in classifying the Gleason grade group (GG) of prostate cancer. Methods: In this retrospective study, a total of 203 patients with histop...

Deskribapen osoa

Xehetasun bibliografikoak

Egile Nagusiak:	Fatemeh Zandie, Mohammad Salehi, Asghar Maziar, Mohammad Reza Bayatiani, Reza Paydar
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	Wolters Kluwer Medknow Publications 2024-12-01
Saila:	Journal of Medical Signals and Sensors
Gaiak:	gleason grading machine learning multiparametric magnetic resonance imaging prostate cancer radiomics
Sarrera elektronikoa:	https://journals.lww.com/10.4103/jmss.jmss_47_23
Etiketak:	Etiketa erantsi Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!