| Literature DB >> 34362709 |
Jethro C C Kwong1, Louise C McLoughlin1, Masoom Haider2, Mitchell G Goldenberg3, Lauren Erdman4, Mandy Rickard5, Armando J Lorenzo6, Andrew J Hung7, Monica Farcas3, Larry Goldenberg8, Chris Nguan8, Luis H Braga9, Muhammad Mamdani10, Anna Goldenberg11, Girish S Kulkarni12.
Abstract
The Standardized Reporting of Machine Learning Applications in Urology (STREAM-URO) framework was developed to provide a set of recommendations to help standardize how machine learning studies in urology are reported. This framework serves three purposes: (1) to promote high-quality studies and streamline the peer review process; (2) to enhance reproducibility, comparability, and interpretability of results; and (3) to improve engagement and literacy of machine learning within the urological community.Entities:
Mesh:
Year: 2021 PMID: 34362709 DOI: 10.1016/j.euf.2021.07.004
Source DB: PubMed Journal: Eur Urol Focus ISSN: 2405-4569