1 research outputs found
Development of a sensory-neural network for medical diagnosing
Performance of a sensory-neural network developed for diagnosing of diseases
is described. Information about patient's condition is provided by answers to
the questionnaire. Questions correspond to sensors generating signals when
patients acknowledge symptoms. These signals excite neurons in which
characteristics of the diseases are represented by synaptic weights associated
with indicators of symptoms. The disease corresponding to the most excited
neuron is proposed as the result of diagnosing. Its reliability is estimated by
the likelihood defined by the ratio of excitation of the most excited neuron
and the complete neural network.Comment: International symposium on neural networks 2018, Minsk, Belarus, June
25-28, 201