TY - JOUR
T1 - Understanding artificial neural networks and exploring their potential applications for the practicing urologist
AU - Wei, John T.
AU - Zhang, Zhen
AU - Barnhill, Stephen D.
AU - Madyastha, K. Rama
AU - Zhang, Hong
AU - Oesterling, Joseph E.
PY - 1998/8/1
Y1 - 1998/8/1
N2 - Artificial neural networks (ANNs) are complex mathematical models that are distantly based on the human neuronal structure. They are capable of modeling elaborate biologic systems without making assumptions based on statistical distributions. Preliminary work has been reported on their application in urology. The initial results have been promising, particularly as an additional tool in the detection of early prostate cancer using the ProstAsure Index, which has been the most extensively studied urologic ANN to date. We review the basic concepts behind ANNs and examine currently existing and potential future applications of this new dynamic technology both in urology and in general clinical medicine.
AB - Artificial neural networks (ANNs) are complex mathematical models that are distantly based on the human neuronal structure. They are capable of modeling elaborate biologic systems without making assumptions based on statistical distributions. Preliminary work has been reported on their application in urology. The initial results have been promising, particularly as an additional tool in the detection of early prostate cancer using the ProstAsure Index, which has been the most extensively studied urologic ANN to date. We review the basic concepts behind ANNs and examine currently existing and potential future applications of this new dynamic technology both in urology and in general clinical medicine.
UR - http://www.scopus.com/inward/record.url?scp=0032146619&partnerID=8YFLogxK
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U2 - 10.1016/S0090-4295(98)00181-2
DO - 10.1016/S0090-4295(98)00181-2
M3 - Review article
C2 - 9697777
AN - SCOPUS:0032146619
SN - 0090-4295
VL - 52
SP - 161
EP - 172
JO - Urology
JF - Urology
IS - 2
ER -