Incorporating artificial intelligence in urology: Supervised machine learning algorithms demonstrate comparative advantage over nomograms in predicting biochemical recurrence after prostatectomy.
Journal:
The Prostate
PMID:
34855228
Abstract
OBJECTIVE: After radical prostatectomy (RP), one-third of patients will experience biochemical recurrence (BCR), which is associated with subsequent metastasis and cancer-specific mortality. We employed machine learning (ML) algorithms to predict BCR after RP, and compare them with traditional regression models and nomograms.
Authors
Keywords
Algorithms
Artificial Intelligence
Biomarkers
Comparative Effectiveness Research
Computer Simulation
Humans
Male
Middle Aged
Neoplasm Metastasis
Neoplasm Staging
Nomograms
Predictive Value of Tests
Prognosis
Prostatectomy
Prostatic Neoplasms
Recurrence
Regression Analysis
Reproducibility of Results
Risk Assessment
Supervised Machine Learning