| Literature DB >> 34776055 |
Andrew B Chen1, Taseen Haque2, Sidney Roberts2, Sirisha Rambhatla3, Giovanni Cacciamani1, Prokar Dasgupta4, Andrew J Hung5.
Abstract
The growth and adoption of artificial intelligence has led to impressive results in urology. As artificial intelligence grows more ubiquitous, it is important to establish artificial intelligence literacy in the workforce. To this end, we present a narrative review of the literature of artificial intelligence and machine learning in urology and propose a checklist of reporting standards to improve readability and evaluate the current state of the literature. The listed article demonstrated heterogeneous reporting of methodologies and outcomes, limiting generalizability of research. We hope that this review serves as a foundation for future evaluation of medical research in artificial intelligence.Entities:
Keywords: Artificial intelligence; Deep learning; Machine learning; Review; Urology
Mesh:
Year: 2021 PMID: 34776055 PMCID: PMC9147289 DOI: 10.1016/j.ucl.2021.07.009
Source DB: PubMed Journal: Urol Clin North Am ISSN: 0094-0143 Impact factor: 2.766