{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Liu Y"],"funding":["Innovative Research Group Project of the National Natural Science Foundation of China","Key-Area Research and Development Program of Guangdong Province","Beijing hospitals Authority 10 Key Construction Projects Funding","Nature Science Foundation of Beijing","Beijing Hospital Authority Clinical Medicine Development special funding support","National Key Research and Development Program of China"],"pagination":["16"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11226574"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["7(1)"],"pubmed_abstract":["Active surveillance (AS) is the primary strategy for managing patients with low or favorable-intermediate risk prostate cancer (PCa). Identifying patients who may benefit from AS relies on unpleasant prostate biopsies, which entail the risk of bleeding and infection. In the current study, we aimed to develop a radiomics model based on prostate magnetic resonance images to identify AS candidates non-invasively. A total of 956 PCa patients with complete biopsy reports from six hospitals were included in the current multicenter retrospective study. The National Comprehensive Cancer Network (NCCN) guidelines were used as reference standards to determine the AS candidacy. To discriminate between AS and non-AS candidates, five radiomics models (i.e., eXtreme Gradient Boosting (XGBoost) AS classi"],"journal":["Visual computing for industry, biomedicine, and art"],"pubmed_title":["Non-invasively identifying candidates of active surveillance for prostate cancer using magnetic resonance imaging radiomics."],"pmcid":["PMC11226574"],"funding_grant_id":["Q19051-16","Z200027","2021B0101420005","81671656","2022YFB3203800","82071887","ZLRK202333"],"pubmed_authors":["Liu J","Shen J","Zhang J","Ji L","Yang B","Liu S","Kang Z","Wang L","Liu Y","Li X","Hou J","Hu C","Zhao L","Jing Z","Bao J","Cao Z"],"additional_accession":[]},"is_claimable":false,"name":"Non-invasively identifying candidates of active surveillance for prostate cancer using magnetic resonance imaging radiomics.","description":"Active surveillance (AS) is the primary strategy for managing patients with low or favorable-intermediate risk prostate cancer (PCa). Identifying patients who may benefit from AS relies on unpleasant prostate biopsies, which entail the risk of bleeding and infection. In the current study, we aimed to develop a radiomics model based on prostate magnetic resonance images to identify AS candidates non-invasively. A total of 956 PCa patients with complete biopsy reports from six hospitals were included in the current multicenter retrospective study. The National Comprehensive Cancer Network (NCCN) guidelines were used as reference standards to determine the AS candidacy. To discriminate between AS and non-AS candidates, five radiomics models (i.e., eXtreme Gradient Boosting (XGBoost) AS classi","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Jul","modification":"2025-04-04T23:54:57.306Z","creation":"2025-04-04T23:54:57.306Z"},"accession":"S-EPMC11226574","cross_references":{"pubmed":["38967824"],"doi":["10.1186/s42492-024-00167-6"]}}