Machine learning methods can more efficiently predict prostate cancer compared with prostate-specific antigen density and prostate-specific antigen velocity
Background: Prostate-specific antigen (PSA)–based screening for prostate cancer has been widely performed, but its accuracy is unsatisfactory. To improve accuracy, building an effective statistical model using machine learning methods (MLMs) is a promising approach. Methods: Data on continuous chang...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2019-09-01
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| Series: | Prostate International |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2287888218301120 |