Clinical applications of artificial intelligence in urologic oncology
- PMID: 32941255
- DOI: 10.1097/MOU.0000000000000819
Clinical applications of artificial intelligence in urologic oncology
Abstract
Purpose of review: This review aims to shed light on recent applications of artificial intelligence in urologic oncology.
Recent findings: Artificial intelligence algorithms harness the wealth of patient data to assist in diagnosing, staging, treating, and monitoring genitourinary malignancies. Successful applications of artificial intelligence in urologic oncology include interpreting diagnostic imaging, pathology, and genomic annotations. Many of these algorithms, however, lack external validity and can only provide predictions based on one type of dataset.
Summary: Future applications of artificial intelligence will need to incorporate several forms of data in order to truly make headway in urologic oncology. Researchers must actively ensure future artificial intelligence developments encompass the entire prospective patient population.
References
-
- Sanders S, Terwiesch M, Gordon W, Stern A. How Artificial Intelligence Is Changing Health Care Delivery. New England Journal Of Medicine Catalyst [Internet]. 2019. Available from: https://catalyst.nejm.org/action/doSearch?AllField=how+artificial+intell....
-
- More than machines. Nat Mach Intell 2019; 1:1–11.
-
- Bolter D. Artificial Intelligence. In: Turing Õs Man: Western Culture in the Computer Age. University of North Carolina Press; 1984. p. 189–213
-
- Lecun Y, Bengio Y, Hinton G. Deep learning. Nature 2015; 521:436–444.
-
- Sagar R. AI for all: The US introduces new bill for affordable research [Internet]. Analyticsindiamag.com. 2020 [cited 2020 Sep 2]. Available from: https://analyticsindiamag.com/us-ai-task-force-act-cheap-cloud-resources/
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Research Materials