A sensory-neural network for medical diagnosis

Abstract

A sensory-neural network for automatic diagnosing of diseases is described. The network gathers information using the patient's answers to a questionnaire. Specific questions correspond to sensors that react when patients acknowledge symptoms. The signals from the sensors stimulate neurons in which the characteristics of the disease are stored in terms of synaptic weights assigned to indicators of symptoms. The response of a neuron is determined by the weighted sum of input stimuli. The disease corresponding to the most excited neuron represents the result of diagnosis. Its reliability is assessed by the likelihood defined as the relative excitation of the neuron with respect to all others. The performance of the network is demonstrated through characteristic examples of diagnosis.