Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\27826573
.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117 Ann+Transl+Med
2016 ; 4
(19
): 370
Nephropedia Template TP
gab.com Text
Twit Text FOAVip
Twit Text #
English Wikipedia
A gentle introduction to artificial neural networks
#MMPMID27826573
Zhang Z
Ann Transl Med
2016[Oct]; 4
(19
): 370
PMID27826573
show ga
Artificial neural network (ANN) is a flexible and powerful machine learning
technique. However, it is under utilized in clinical medicine because of its
technical challenges. The article introduces some basic ideas behind ANN and
shows how to build ANN using R in a step-by-step framework. In topology and
function, ANN is in analogue to the human brain. There are input and output
signals transmitting from input to output nodes. Input signals are weighted
before reaching output nodes according to their respective importance. Then the
combined signal is processed by activation function. I simulated a simple example
to illustrate how to build a simple ANN model using nnet() function. This
function allows for one hidden layer with varying number of units in that layer.
The basic structure of ANN can be visualized with plug-in plot.nnet() function.
The plot function is powerful that it allows for varieties of adjustment to the
appearance of the neural networks. Prediction with ANN can be performed with
predict() function, similar to that of conventional generalized linear models.
Finally, the prediction power of ANN is examined using confusion matrix and
average accuracy. It appears that ANN is slightly better than conventional linear
model.
free
free
free
