Journal article

Predicting prostate biopsy outcome: artificial neural networks and polychotomous regression are equivalent models

Nathan Lawrentschuk, Gina Lockwood, Peter Davies, Andy Evans, Joan Sweet, Ants Toi, Neil E Fleshner

Urology | SPRINGER | Published : 2011

DOI: 10.1007/s11255-010-9750-7

University of Melbourne Researchers

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Keywords

Incidence
Logistic Models
Adult
Ontario
Endosonography
Life Sciences & Biomedicine
Age Distribution
Predictive Value of Tests
Middle Aged
Antigen
Male
Risk Assessment
Preoperative Nomogram
Cancer
Aged
Retrospective Studies
Biopsy
Patient
Neural Network
Mortality
Treatment Outcome
Follow-Up Studies
Intraepithelial Neoplasia
Prostatic Neoplasms
Digital Rectal Examination
Neoplasm Staging
Radical Prostatectomy
Prostate Cancer
Validation
Diagnosis
Statistics
Age Factors
Neural Networks, Computer
Humans
Urology & Nephrology
Prostate
Neural Networks (computer)
Science & Technology
Aged, 80 and Over