Artificial neural networks and prostate cancer--tools for diagnosis and management.
Nat Rev Urol
; 10(3): 174-82, 2013 Mar.
Article
in En
| MEDLINE
| ID: mdl-23399728
ABSTRACT
Artificial neural networks (ANNs) are mathematical models that are based on biological neural networks and are composed of interconnected groups of artificial neurons. ANNs are used to map and predict outcomes in complex relationships between given 'inputs' and sought-after 'outputs' and can also be used find patterns in datasets. In medicine, ANN applications have been used in cancer diagnosis, staging and recurrence prediction since the mid-1990s, when an enormous effort was initiated, especially in prostate cancer detection. Modern ANNs can incorporate new biomarkers and imaging data to improve their predictive power and can offer a number of advantages as clinical decision making tools, such as easy handling of distribution-free input parameters. Most importantly, ANNs consider nonlinear relationships among input data that cannot always be recognized by conventional analyses. In the future, complex medical diagnostic and treatment decisions will be increasingly based on ANNs and other multivariate models.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Prostatic Neoplasms
/
Neural Networks, Computer
Type of study:
Diagnostic_studies
/
Prognostic_studies
Limits:
Humans
/
Male
Language:
En
Journal:
Nat Rev Urol
Journal subject:
UROLOGIA
Year:
2013
Document type:
Article
Affiliation country: