The use of artificial neural networks in biomedical technologies: an introduction.
Artificial neural networks (NN) are systems than can learn. In the most common situation, an operator trains the system on a set of input and output data belonging to a particular category. If new data of the same category, but not in the training set, are presented to the system, the NN can use the learned data to predict outcomes without any specific programming relating to the category of events involved. The fields of application of NN have increased dramatically in the past few years. Originally, the NN technique was mainly in the hands of computer programming specialists and the applications concentrated on tasks such as decision systems and signal processing. However, this picture has changed due to the emergence of user-friendly NN software for personal computers. A large variety of possible NN applications now exist for non-computer specialists. Thus, with only a very modest knowledge of the theory behind neural networks, it is possible to attack complicated problems in a researcher's own area of specialty with the NN technique. This is especially true in the field of medical technology, the topic of this review. The review is divided into three sections: 1) an elementary introduction to useful NN methods; 2) a review of the most important applications of the NN technique to this point in time; 3) a summary of available computer details that would be needed for a beginner in this field.
Alvager
T
T
Department of Physics, Indiana State University, Terre Haute 47809.
Smith
T J
TJ
Vijai
F
F
D006801:Humans; D007091:Image Processing, Computer-Assisted; D013677:Medical Laboratory Science; D016571:Neural Networks, Computer; D012984:Software; D018581:Technology Transfer