Author:
Couchoux Thibaut,Jaouen Tristan,Melodelima-Gonindard Christelle,Baseilhac Pierre,Branchu Arthur,Arfi Nicolas,Aziza Richard,Barry Delongchamps Nicolas,Bladou Franck,Bratan Flavie,Brunelle Serge,Colin Pierre,Correas Jean-Michel,Cornud François,Descotes Jean-Luc,Eschwege Pascal,Fiard Gaelle,Guillaume Bénédicte,Grange Rémi,Grenier Nicolas,Lang Hervé,Lefèvre Frédéric,Malavaud Bernard,Marcelin Clément,Moldovan Paul C.,Mottet Nicolas,Mozer Pierre,Potiron Eric,Portalez Daniel,Puech Philippe,Renard-Penna Raphaele,Roumiguié Matthieu,Roy Catherine,Timsit Marc-Olivier,Tricard Thibault,Villers Arnauld,Walz Jochen,Debeer Sabine,Mansuy Adeline,Mège-Lechevallier Florence,Decaussin-Petrucci Myriam,Badet Lionel,Colombel Marc,Ruffion Alain,Crouzet Sébastien,Rabilloud Muriel,Souchon Rémi,Rouvière Olivier
Funder
French National Research Agency
Reference36 articles.
1. Prostate MRI, with or without MRI-targeted biopsy, and systematic biopsy for detecting prostate cancer;Drost;Cochrane Database Syst Rev,2019
2. Artificial intelligence compared to radiologists for the initial diagnosis of prostate cancer on magnetic resonance imaging: A systematic review and recommendations for future studies;Syer;Cancers,2021
3. Artificial intelligence algorithms aimed at characterizing or detecting prostate cancer on MRI: how accurate are they when tested on independent cohorts?—A systematic review;Rouviere;Diagn Interv Imaging,2023
4. Comparative performance of fully-automated and semi-automated artificial intelligence methods for the detection of clinically significant prostate cancer on MRI: a systematic review. Insights;Sushentsev;Imaging,2022
5. Repeatability of multiparametric prostate MRI radiomics features;Schwier;Sci Rep,2019