Multi Model Implementation on General Medicine Prediction with Quantum Neural Networks

Medical is the large-scale repository where there is more chances to create a new model in the zone of prediction. The proposed methodology mentioned in this article speaks about the general medicine prediction using QNN which is a challenging factor in the prediction model design and implementation. The main cause of predicting the general medicine is to predict the accurate medical combination for the patient who needs some medication and doesn't find the accurate medication in pharmacy or with the druggist. The proposed methodology with QNN is having the option to predict the accurate general medicine for the patient with some disease factors as the symptoms. The accuracy achieved is 92% with the neural network which is a hybrid mechanism with the initial data factors are considered using the expert systems. The concept of expert systems is required in this mechanism because frames are being used in this proposed architecture related to the medicine prediction. Using frames, we can make the combination of the drugs and predict the accurate mechanism to check the alternate general medicine which is no harm to the patient until he or she gets the medical support. This general medicine prediction will be the standby process for the patient who requires the medication immediately and not able to get the accurate medicines from the nearest pharmacy.